trim to the all_5gb_cutoff databases (50/116 removed)
Browse filesThis view is limited to 50 files because it contains too many changes. See raw diff
- join-amazon-electronics/column_index.json +0 -1
- join-amazon-electronics/meta.json +0 -750
- join-amazon-electronics/nodes.rkyv +0 -3
- join-amazon-electronics/offsets.rkyv +0 -3
- join-amazon-electronics/p2f_adj.rkyv +0 -3
- join-amazon-electronics/table_info.json +0 -1
- join-amazon-electronics/text.json +0 -3
- join-amazon-electronics/text_emb_all-MiniLM-L12-v2.bin +0 -3
- join-amazon-fashion/column_index.json +0 -1
- join-amazon-fashion/meta.json +0 -710
- join-amazon-fashion/nodes.rkyv +0 -3
- join-amazon-fashion/offsets.rkyv +0 -3
- join-amazon-fashion/p2f_adj.rkyv +0 -3
- join-amazon-fashion/table_info.json +0 -1
- join-amazon-fashion/text.json +0 -3
- join-amazon-fashion/text_emb_all-MiniLM-L12-v2.bin +0 -3
- join-amazon-movies/column_index.json +0 -1
- join-amazon-movies/meta.json +0 -664
- join-amazon-movies/nodes.rkyv +0 -3
- join-amazon-movies/offsets.rkyv +0 -3
- join-amazon-movies/p2f_adj.rkyv +0 -3
- join-amazon-movies/table_info.json +0 -1
- join-amazon-movies/text.json +0 -0
- join-amazon-movies/text_emb_all-MiniLM-L12-v2.bin +0 -3
- join-amazon-sports/column_index.json +0 -1
- join-amazon-sports/meta.json +0 -772
- join-amazon-sports/nodes.rkyv +0 -3
- join-amazon-sports/offsets.rkyv +0 -3
- join-amazon-sports/p2f_adj.rkyv +0 -3
- join-amazon-sports/table_info.json +0 -1
- join-amazon-sports/text.json +0 -3
- join-amazon-sports/text_emb_all-MiniLM-L12-v2.bin +0 -3
- join-amazon0302/column_index.json +0 -1
- join-amazon0302/meta.json +0 -24
- join-amazon0302/nodes.rkyv +0 -3
- join-amazon0302/offsets.rkyv +0 -3
- join-amazon0302/p2f_adj.rkyv +0 -3
- join-amazon0302/table_info.json +0 -1
- join-amazon0302/text.json +0 -1
- join-amazon0302/text_emb_all-MiniLM-L12-v2.bin +0 -3
- join-arnaud-citeseer/column_index.json +0 -1
- join-arnaud-citeseer/meta.json +0 -24
- join-arnaud-citeseer/nodes.rkyv +0 -3
- join-arnaud-citeseer/offsets.rkyv +0 -3
- join-arnaud-citeseer/p2f_adj.rkyv +0 -3
- join-arnaud-citeseer/table_info.json +0 -1
- join-arnaud-citeseer/text.json +0 -1
- join-arnaud-citeseer/text_emb_all-MiniLM-L12-v2.bin +0 -3
- join-beeradvocate/column_index.json +0 -1
- join-beeradvocate/meta.json +0 -761
join-amazon-electronics/column_index.json
DELETED
|
@@ -1 +0,0 @@
|
|
| 1 |
-
{"product_id of product-avg-review-length":14,"reviewer_id of reviewer-time-until-next-h4":493999,"days_to_next_h4 of reviewer-time-until-next-h4":494000,"reviewer_id of reviewer-return":494003,"product_id of product-churn-h4":493959,"timestamp of reviewer-rating-sum":493917,"rating_sum of reviewer-rating-sum":493916,"category of products":111571,"reviewer_id of reviewer-mean-rating":492884,"timestamp of product-max-review-length":33,"timestamp of product-churn":493992,"product_id of product-max-review-length":31,"timestamp of product-return-h4":493988,"rating_trend of product-rating-trend":494016,"product_id of product-time-until-next-h6":10,"product_id of products":42,"timestamp of reviewer-return-h6":492809,"timestamp of reviewer-verified-ratio":493921,"timestamp of reviewer-distinct-products":493929,"product_id of reviews":492888,"timestamp of product-long-review":494009,"reviewed_next of product-will-be-reviewed":493977,"reviewer_id of reviewer-long-writer":111580,"reviewer_id of reviewer-max-review-len":492800,"reviewer_min_rating of reviewer-min-rating":492841,"timestamp of reviewer-churn-h4":493912,"timestamp of product-min-rating":111578,"timestamp of reviewer-time-until-next-h8":493953,"days_to_next_h6 of product-time-until-next-h6":11,"low_rating_event of product-low-rating-event":492845,"timestamp of product-time-until-next-h6":12,"reviewer_max_len of reviewer-max-review-len":492801,"days_to_next_h8 of product-time-until-next-h8":492833,"timestamp of product-any-new-review":492821,"verified of reviews":492891,"churned_h4 of product-churn-h4":493961,"timestamp of reviewer-long-review-writer":493969,"timestamp of product-unique-reviewers":492838,"product_id of product-will-be-reviewed":493975,"returned_h8 of reviewer-return-h8":25,"timestamp of reviewer-long-writer":111582,"timestamp of reviewer-churn":492849,"timestamp of product-review-count":37,"predict_reviewer_churn of reviewer-churn":492850,"reviewer_id of reviewer-rating-trend":492852,"reviewer_id of reviewer-churn-h6":493939,"timestamp of reviewer-time-until-next-h5":493945,"timestamp of product-churn-h6":493984,"returned_h4 of product-return-h4":493989,"timestamp of reviews":492890,"reviewer_name of reviewers":111584,"timestamp of reviewer-churn-h8":493996,"product_id of product-mean-rating":494011,"reviewer_id of reviewer-min-rating":492840,"churned_h4 of reviewer-churn-h4":493913,"reviewer_id of reviewer-distinct-products":493927,"verbose_reviewer of reviewer-long-review-writer":493968,"timestamp of product-mean-rating":494013,"predict_product_review_count of product-review-count":36,"reviewer_range of product-unique-reviewers":492837,"product_id of product-unique-reviewers":492836,"churned_h5 of reviewer-churn-h5":493933,"product_id of product-min-rating":111576,"product_id of product-popular-next-window":493963,"churned_h6 of product-churn-h6":493985,"vote of reviews":492892,"reviewer_id of reviewer-will-review-product":492816,"product_id of product-all-verified":492868,"min_rating of product-min-rating":111577,"timestamp of reviewer-mean-rating":492886,"pred_rating of product-mean-rating":494012,"brand of products":100598,"timestamp of reviewer-review-count":493957,"title of products":43,"pred_verified of reviewer-verified-ratio":493920,"price of products":111570,"timestamp of reviewer-verified-only":492858,"product_id of product-return-h8":492872,"harsh_critic of reviewer-harsh-critic":492825,"timestamp of product-rating-trend":494017,"timestamp of product-return-h6":3,"timestamp of product-verified-share":492878,"timestamp of product-return-h8":492873,"timestamp of product-time-until-next-h8":492834,"timestamp of reviewer-min-rating":492842,"book_has_review of product-any-new-review":492822,"returned_h4 of reviewer-return-h4":493937,"reviewer_id of reviewer-churn-h8":493995,"long_review of product-long-review":494008,"product_id of product-verified-count":18,"churned_h8 of product-churn-h8":493981,"reviewer_id of reviewer-rating-sum":493915,"pred_rating of reviewer-mean-rating":492885,"reviewer_id of reviewer-return-h4":493935,"timestamp of reviewer-return-h5":493972,"product_id of product-rating-volatility":492828,"distinct_products of reviewer-distinct-products":493928,"timestamp of reviewer-will-review-product":492817,"timestamp of product-rating-volatility":492830,"rating_volatility of product-rating-volatility":492829,"timestamp of product-max-review-len":493925,"verified_count of product-verified-count":19,"timestamp of reviewer-avg-review-length":41,"timestamp of reviewer-review-3w":492814,"product_id of product-review-count":35,"n_reviews of products":111574,"timestamp of reviewer-return-h8":24,"reviews_next of reviewer-will-review-product":492818,"reviewer_id of reviewer-verified-ratio":493919,"timestamp of reviewer-churn-h6":493940,"timestamp of product-low-rating-event":492846,"product_id of product-review-length-change":492864,"returned_h8 of product-return-h8":492874,"timestamp of reviewer-time-until-next-h6":493949,"reviewer_id of reviewer-review-count":493955,"timestamp of product-churn-h8":493980,"days_to_next_h5 of reviewer-time-until-next-h5":493944,"predict_product_churn of product-churn":493993,"reviewer_returns of reviewer-return":494005,"product_id of product-long-review":494007,"timestamp of reviewer-max-rating":492882,"churned_h8 of reviewer-churn-h8":493997,"low_rating of product-low-rating":492805,"reviewer_id of reviewer-churn":492848,"reviewer_max_rating of reviewer-max-rating":492881,"timestamp of reviewer-harsh-critic":492826,"product_returns of product-return":29,"timestamp of product-low-rating":492806,"timestamp of product-review-length-change":492866,"review_len of reviews":493909,"avg_review_len of reviewer-avg-review-length":40,"reviewer_id of reviewer-avg-review-length":39,"reviewer_id of reviewers":111583,"returned_h6 of reviewer-return-h6":492810,"product_id of product-low-rating":492804,"reviewer_id of reviewer-harsh-critic":492824,"product_id of product-low-rating-event":492844,"reviewer_id of reviewer-verified-only":492856,"product_id of product-return-h6":1,"reviewer_id of reviewer-churn-h4":493911,"product_id of product-return":27,"max_review_len of product-max-review-len":493924,"rating_sum of product-total-rating-sum":7,"timestamp of product-total-rating-sum":8,"timestamp of reviewer-churn-h5":493932,"verified_rate of product-verified-share":492877,"reviewer_id of reviewer-return-h6":492808,"days_to_next_h6 of reviewer-time-until-next-h6":493948,"timestamp of product-churn-h4":493960,"reviewer_rating_trend of reviewer-rating-trend":492853,"timestamp of product-top-review-volume":492862,"avg_review_len of product-avg-review-length":15,"days_to_next_h8 of reviewer-time-until-next-h8":493952,"product_id of product-verified-share":492876,"reviewer_id of reviewer-long-review-writer":493967,"reviewer_id of reviewer-return-h5":493971,"reviewer_id of reviewer-time-until-next-h8":493951,"returned_h5 of reviewer-return-h5":493973,"reviewer_id of reviewer-max-rating":492880,"product_id of product-time-until-next-h8":492832,"predict_reviewer_review_count of reviewer-review-count":493956,"all_verified of product-all-verified":492869,"timestamp of reviewer-return-h4":493936,"churned_h6 of reviewer-churn-h6":493941,"reviewer_id of reviewer-time-until-next-h5":493943,"reviewer_id of reviewer-review-3w":492812,"reviewer_id of reviewer-return-h8":22,"timestamp of product-verified-count":20,"all_verified_reviewer of reviewer-verified-only":492857,"product_id of product-top-review-volume":492860,"timestamp of reviewer-rating-trend":492854,"rating of reviews":492889,"product_id of product-max-review-len":493923,"reviewer_3w of reviewer-review-3w":492813,"max_review_len of product-max-review-length":32,"timestamp of product-all-verified":492870,"reviewer_id of reviewer-churn-h5":493931,"product_id of product-any-new-review":492820,"review_length_change of product-review-length-change":492865,"product_id of product-total-rating-sum":6,"timestamp of reviewer-max-review-len":492802,"reviewer_id of reviews":492887,"popular of product-popular-next-window":493964,"reviewer_id of reviewer-time-until-next-h6":493947,"timestamp of product-popular-next-window":493965,"timestamp of product-will-be-reviewed":493976,"timestamp of product-return":28,"product_id of product-churn-h6":493983,"product_id of product-churn":493991,"timestamp of reviewer-time-until-next-h4":494001,"timestamp of reviewer-return":494004,"long_writer of reviewer-long-writer":111581,"timestamp of product-avg-review-length":16,"product_id of product-rating-trend":494015,"top_review_volume of product-top-review-volume":492861,"returned_h6 of product-return-h6":4,"avg_rating of products":111573,"product_id of product-churn-h8":493979,"product_id of product-return-h4":493987}
|
|
|
|
|
|
join-amazon-electronics/meta.json
DELETED
|
@@ -1,750 +0,0 @@
|
|
| 1 |
-
{
|
| 2 |
-
"files": {
|
| 3 |
-
"column_index": "column_index.json",
|
| 4 |
-
"nodes": "nodes.rkyv",
|
| 5 |
-
"offsets": "offsets.rkyv",
|
| 6 |
-
"p2f_adj": "p2f_adj.rkyv",
|
| 7 |
-
"table_info": "table_info.json",
|
| 8 |
-
"text": "text.json"
|
| 9 |
-
},
|
| 10 |
-
"format_version": 1,
|
| 11 |
-
"name": "join-amazon-electronics",
|
| 12 |
-
"num_db_tables": 3,
|
| 13 |
-
"num_nodes": 68994236,
|
| 14 |
-
"num_task_tables": 61,
|
| 15 |
-
"num_text_strings": 494018,
|
| 16 |
-
"source": "stanford-star/the-join/join-amazon-electronics",
|
| 17 |
-
"tasks": [
|
| 18 |
-
{
|
| 19 |
-
"entity_table": "products",
|
| 20 |
-
"kind": "forecast",
|
| 21 |
-
"name": "product-all-verified",
|
| 22 |
-
"splits": [
|
| 23 |
-
"train"
|
| 24 |
-
],
|
| 25 |
-
"target_col": "all_verified",
|
| 26 |
-
"task_type": "binary_classification",
|
| 27 |
-
"time_col": "timestamp"
|
| 28 |
-
},
|
| 29 |
-
{
|
| 30 |
-
"entity_table": "products",
|
| 31 |
-
"kind": "forecast",
|
| 32 |
-
"name": "product-any-new-review",
|
| 33 |
-
"splits": [
|
| 34 |
-
"train"
|
| 35 |
-
],
|
| 36 |
-
"target_col": "book_has_review",
|
| 37 |
-
"task_type": "binary_classification",
|
| 38 |
-
"time_col": "timestamp"
|
| 39 |
-
},
|
| 40 |
-
{
|
| 41 |
-
"entity_table": "products",
|
| 42 |
-
"kind": "forecast",
|
| 43 |
-
"name": "product-avg-review-length",
|
| 44 |
-
"splits": [
|
| 45 |
-
"train"
|
| 46 |
-
],
|
| 47 |
-
"target_col": "avg_review_len",
|
| 48 |
-
"task_type": "regression",
|
| 49 |
-
"time_col": "timestamp"
|
| 50 |
-
},
|
| 51 |
-
{
|
| 52 |
-
"entity_table": "products",
|
| 53 |
-
"kind": "forecast",
|
| 54 |
-
"name": "product-churn",
|
| 55 |
-
"splits": [
|
| 56 |
-
"train"
|
| 57 |
-
],
|
| 58 |
-
"target_col": "predict_product_churn",
|
| 59 |
-
"task_type": "binary_classification",
|
| 60 |
-
"time_col": "timestamp"
|
| 61 |
-
},
|
| 62 |
-
{
|
| 63 |
-
"entity_table": "products",
|
| 64 |
-
"kind": "forecast",
|
| 65 |
-
"name": "product-churn-h4",
|
| 66 |
-
"splits": [
|
| 67 |
-
"train"
|
| 68 |
-
],
|
| 69 |
-
"target_col": "churned_h4",
|
| 70 |
-
"task_type": "binary_classification",
|
| 71 |
-
"time_col": "timestamp"
|
| 72 |
-
},
|
| 73 |
-
{
|
| 74 |
-
"entity_table": "products",
|
| 75 |
-
"kind": "forecast",
|
| 76 |
-
"name": "product-churn-h6",
|
| 77 |
-
"splits": [
|
| 78 |
-
"train"
|
| 79 |
-
],
|
| 80 |
-
"target_col": "churned_h6",
|
| 81 |
-
"task_type": "binary_classification",
|
| 82 |
-
"time_col": "timestamp"
|
| 83 |
-
},
|
| 84 |
-
{
|
| 85 |
-
"entity_table": "products",
|
| 86 |
-
"kind": "forecast",
|
| 87 |
-
"name": "product-churn-h8",
|
| 88 |
-
"splits": [
|
| 89 |
-
"train"
|
| 90 |
-
],
|
| 91 |
-
"target_col": "churned_h8",
|
| 92 |
-
"task_type": "binary_classification",
|
| 93 |
-
"time_col": "timestamp"
|
| 94 |
-
},
|
| 95 |
-
{
|
| 96 |
-
"entity_table": "products",
|
| 97 |
-
"kind": "forecast",
|
| 98 |
-
"name": "product-long-review",
|
| 99 |
-
"splits": [
|
| 100 |
-
"train"
|
| 101 |
-
],
|
| 102 |
-
"target_col": "long_review",
|
| 103 |
-
"task_type": "binary_classification",
|
| 104 |
-
"time_col": "timestamp"
|
| 105 |
-
},
|
| 106 |
-
{
|
| 107 |
-
"entity_table": "products",
|
| 108 |
-
"kind": "forecast",
|
| 109 |
-
"name": "product-low-rating",
|
| 110 |
-
"splits": [
|
| 111 |
-
"train"
|
| 112 |
-
],
|
| 113 |
-
"target_col": "low_rating",
|
| 114 |
-
"task_type": "binary_classification",
|
| 115 |
-
"time_col": "timestamp"
|
| 116 |
-
},
|
| 117 |
-
{
|
| 118 |
-
"entity_table": "products",
|
| 119 |
-
"kind": "forecast",
|
| 120 |
-
"name": "product-low-rating-event",
|
| 121 |
-
"splits": [
|
| 122 |
-
"train"
|
| 123 |
-
],
|
| 124 |
-
"target_col": "low_rating_event",
|
| 125 |
-
"task_type": "binary_classification",
|
| 126 |
-
"time_col": "timestamp"
|
| 127 |
-
},
|
| 128 |
-
{
|
| 129 |
-
"entity_table": "products",
|
| 130 |
-
"kind": "forecast",
|
| 131 |
-
"name": "product-max-review-len",
|
| 132 |
-
"splits": [
|
| 133 |
-
"train"
|
| 134 |
-
],
|
| 135 |
-
"target_col": "max_review_len",
|
| 136 |
-
"task_type": "regression",
|
| 137 |
-
"time_col": "timestamp"
|
| 138 |
-
},
|
| 139 |
-
{
|
| 140 |
-
"entity_table": "products",
|
| 141 |
-
"kind": "forecast",
|
| 142 |
-
"name": "product-max-review-length",
|
| 143 |
-
"splits": [
|
| 144 |
-
"train"
|
| 145 |
-
],
|
| 146 |
-
"target_col": "max_review_len",
|
| 147 |
-
"task_type": "regression",
|
| 148 |
-
"time_col": "timestamp"
|
| 149 |
-
},
|
| 150 |
-
{
|
| 151 |
-
"entity_table": "products",
|
| 152 |
-
"kind": "forecast",
|
| 153 |
-
"name": "product-mean-rating",
|
| 154 |
-
"splits": [
|
| 155 |
-
"train"
|
| 156 |
-
],
|
| 157 |
-
"target_col": "pred_rating",
|
| 158 |
-
"task_type": "regression",
|
| 159 |
-
"time_col": "timestamp"
|
| 160 |
-
},
|
| 161 |
-
{
|
| 162 |
-
"entity_table": "products",
|
| 163 |
-
"kind": "forecast",
|
| 164 |
-
"name": "product-min-rating",
|
| 165 |
-
"splits": [
|
| 166 |
-
"train"
|
| 167 |
-
],
|
| 168 |
-
"target_col": "min_rating",
|
| 169 |
-
"task_type": "regression",
|
| 170 |
-
"time_col": "timestamp"
|
| 171 |
-
},
|
| 172 |
-
{
|
| 173 |
-
"entity_table": "products",
|
| 174 |
-
"kind": "forecast",
|
| 175 |
-
"name": "product-popular-next-window",
|
| 176 |
-
"splits": [
|
| 177 |
-
"train"
|
| 178 |
-
],
|
| 179 |
-
"target_col": "popular",
|
| 180 |
-
"task_type": "binary_classification",
|
| 181 |
-
"time_col": "timestamp"
|
| 182 |
-
},
|
| 183 |
-
{
|
| 184 |
-
"entity_table": "products",
|
| 185 |
-
"kind": "forecast",
|
| 186 |
-
"name": "product-rating-trend",
|
| 187 |
-
"splits": [
|
| 188 |
-
"train"
|
| 189 |
-
],
|
| 190 |
-
"target_col": "rating_trend",
|
| 191 |
-
"task_type": "binary_classification",
|
| 192 |
-
"time_col": "timestamp"
|
| 193 |
-
},
|
| 194 |
-
{
|
| 195 |
-
"entity_table": "products",
|
| 196 |
-
"kind": "forecast",
|
| 197 |
-
"name": "product-rating-volatility",
|
| 198 |
-
"splits": [
|
| 199 |
-
"train"
|
| 200 |
-
],
|
| 201 |
-
"target_col": "rating_volatility",
|
| 202 |
-
"task_type": "regression",
|
| 203 |
-
"time_col": "timestamp"
|
| 204 |
-
},
|
| 205 |
-
{
|
| 206 |
-
"entity_table": "products",
|
| 207 |
-
"kind": "forecast",
|
| 208 |
-
"name": "product-return",
|
| 209 |
-
"splits": [
|
| 210 |
-
"train"
|
| 211 |
-
],
|
| 212 |
-
"target_col": "product_returns",
|
| 213 |
-
"task_type": "binary_classification",
|
| 214 |
-
"time_col": "timestamp"
|
| 215 |
-
},
|
| 216 |
-
{
|
| 217 |
-
"entity_table": "products",
|
| 218 |
-
"kind": "forecast",
|
| 219 |
-
"name": "product-return-h4",
|
| 220 |
-
"splits": [
|
| 221 |
-
"train"
|
| 222 |
-
],
|
| 223 |
-
"target_col": "returned_h4",
|
| 224 |
-
"task_type": "binary_classification",
|
| 225 |
-
"time_col": "timestamp"
|
| 226 |
-
},
|
| 227 |
-
{
|
| 228 |
-
"entity_table": "products",
|
| 229 |
-
"kind": "forecast",
|
| 230 |
-
"name": "product-return-h6",
|
| 231 |
-
"splits": [
|
| 232 |
-
"train"
|
| 233 |
-
],
|
| 234 |
-
"target_col": "returned_h6",
|
| 235 |
-
"task_type": "binary_classification",
|
| 236 |
-
"time_col": "timestamp"
|
| 237 |
-
},
|
| 238 |
-
{
|
| 239 |
-
"entity_table": "products",
|
| 240 |
-
"kind": "forecast",
|
| 241 |
-
"name": "product-return-h8",
|
| 242 |
-
"splits": [
|
| 243 |
-
"train"
|
| 244 |
-
],
|
| 245 |
-
"target_col": "returned_h8",
|
| 246 |
-
"task_type": "binary_classification",
|
| 247 |
-
"time_col": "timestamp"
|
| 248 |
-
},
|
| 249 |
-
{
|
| 250 |
-
"entity_table": "products",
|
| 251 |
-
"kind": "forecast",
|
| 252 |
-
"name": "product-review-count",
|
| 253 |
-
"splits": [
|
| 254 |
-
"train"
|
| 255 |
-
],
|
| 256 |
-
"target_col": "predict_product_review_count",
|
| 257 |
-
"task_type": "regression",
|
| 258 |
-
"time_col": "timestamp"
|
| 259 |
-
},
|
| 260 |
-
{
|
| 261 |
-
"entity_table": "products",
|
| 262 |
-
"kind": "forecast",
|
| 263 |
-
"name": "product-review-length-change",
|
| 264 |
-
"splits": [
|
| 265 |
-
"train"
|
| 266 |
-
],
|
| 267 |
-
"target_col": "review_length_change",
|
| 268 |
-
"task_type": "regression",
|
| 269 |
-
"time_col": "timestamp"
|
| 270 |
-
},
|
| 271 |
-
{
|
| 272 |
-
"entity_table": "products",
|
| 273 |
-
"kind": "forecast",
|
| 274 |
-
"name": "product-time-until-next-h6",
|
| 275 |
-
"splits": [
|
| 276 |
-
"train"
|
| 277 |
-
],
|
| 278 |
-
"target_col": "days_to_next_h6",
|
| 279 |
-
"task_type": "regression",
|
| 280 |
-
"time_col": "timestamp"
|
| 281 |
-
},
|
| 282 |
-
{
|
| 283 |
-
"entity_table": "products",
|
| 284 |
-
"kind": "forecast",
|
| 285 |
-
"name": "product-time-until-next-h8",
|
| 286 |
-
"splits": [
|
| 287 |
-
"train"
|
| 288 |
-
],
|
| 289 |
-
"target_col": "days_to_next_h8",
|
| 290 |
-
"task_type": "regression",
|
| 291 |
-
"time_col": "timestamp"
|
| 292 |
-
},
|
| 293 |
-
{
|
| 294 |
-
"entity_table": "products",
|
| 295 |
-
"kind": "forecast",
|
| 296 |
-
"name": "product-top-review-volume",
|
| 297 |
-
"splits": [
|
| 298 |
-
"train"
|
| 299 |
-
],
|
| 300 |
-
"target_col": "top_review_volume",
|
| 301 |
-
"task_type": "binary_classification",
|
| 302 |
-
"time_col": "timestamp"
|
| 303 |
-
},
|
| 304 |
-
{
|
| 305 |
-
"entity_table": "products",
|
| 306 |
-
"kind": "forecast",
|
| 307 |
-
"name": "product-total-rating-sum",
|
| 308 |
-
"splits": [
|
| 309 |
-
"train"
|
| 310 |
-
],
|
| 311 |
-
"target_col": "rating_sum",
|
| 312 |
-
"task_type": "regression",
|
| 313 |
-
"time_col": "timestamp"
|
| 314 |
-
},
|
| 315 |
-
{
|
| 316 |
-
"entity_table": "products",
|
| 317 |
-
"kind": "forecast",
|
| 318 |
-
"name": "product-unique-reviewers",
|
| 319 |
-
"splits": [
|
| 320 |
-
"train"
|
| 321 |
-
],
|
| 322 |
-
"target_col": "reviewer_range",
|
| 323 |
-
"task_type": "regression",
|
| 324 |
-
"time_col": "timestamp"
|
| 325 |
-
},
|
| 326 |
-
{
|
| 327 |
-
"entity_table": "products",
|
| 328 |
-
"kind": "forecast",
|
| 329 |
-
"name": "product-verified-count",
|
| 330 |
-
"splits": [
|
| 331 |
-
"train"
|
| 332 |
-
],
|
| 333 |
-
"target_col": "verified_count",
|
| 334 |
-
"task_type": "regression",
|
| 335 |
-
"time_col": "timestamp"
|
| 336 |
-
},
|
| 337 |
-
{
|
| 338 |
-
"entity_table": "products",
|
| 339 |
-
"kind": "forecast",
|
| 340 |
-
"name": "product-verified-share",
|
| 341 |
-
"splits": [
|
| 342 |
-
"train"
|
| 343 |
-
],
|
| 344 |
-
"target_col": "verified_rate",
|
| 345 |
-
"task_type": "regression",
|
| 346 |
-
"time_col": "timestamp"
|
| 347 |
-
},
|
| 348 |
-
{
|
| 349 |
-
"entity_table": "products",
|
| 350 |
-
"kind": "forecast",
|
| 351 |
-
"name": "product-will-be-reviewed",
|
| 352 |
-
"splits": [
|
| 353 |
-
"train"
|
| 354 |
-
],
|
| 355 |
-
"target_col": "reviewed_next",
|
| 356 |
-
"task_type": "binary_classification",
|
| 357 |
-
"time_col": "timestamp"
|
| 358 |
-
},
|
| 359 |
-
{
|
| 360 |
-
"entity_table": "products",
|
| 361 |
-
"kind": "autocomplete",
|
| 362 |
-
"name": "products-avg_rating",
|
| 363 |
-
"splits": [],
|
| 364 |
-
"target_col": "avg_rating",
|
| 365 |
-
"task_type": "regression",
|
| 366 |
-
"time_col": null
|
| 367 |
-
},
|
| 368 |
-
{
|
| 369 |
-
"entity_table": "products",
|
| 370 |
-
"kind": "autocomplete",
|
| 371 |
-
"name": "products-n_reviews",
|
| 372 |
-
"splits": [],
|
| 373 |
-
"target_col": "n_reviews",
|
| 374 |
-
"task_type": "regression",
|
| 375 |
-
"time_col": null
|
| 376 |
-
},
|
| 377 |
-
{
|
| 378 |
-
"entity_table": "products",
|
| 379 |
-
"kind": "autocomplete",
|
| 380 |
-
"name": "products-price",
|
| 381 |
-
"splits": [],
|
| 382 |
-
"target_col": "price",
|
| 383 |
-
"task_type": "regression",
|
| 384 |
-
"time_col": null
|
| 385 |
-
},
|
| 386 |
-
{
|
| 387 |
-
"entity_table": "reviewers",
|
| 388 |
-
"kind": "forecast",
|
| 389 |
-
"name": "reviewer-avg-review-length",
|
| 390 |
-
"splits": [
|
| 391 |
-
"train"
|
| 392 |
-
],
|
| 393 |
-
"target_col": "avg_review_len",
|
| 394 |
-
"task_type": "regression",
|
| 395 |
-
"time_col": "timestamp"
|
| 396 |
-
},
|
| 397 |
-
{
|
| 398 |
-
"entity_table": "reviewers",
|
| 399 |
-
"kind": "forecast",
|
| 400 |
-
"name": "reviewer-churn",
|
| 401 |
-
"splits": [
|
| 402 |
-
"train"
|
| 403 |
-
],
|
| 404 |
-
"target_col": "predict_reviewer_churn",
|
| 405 |
-
"task_type": "binary_classification",
|
| 406 |
-
"time_col": "timestamp"
|
| 407 |
-
},
|
| 408 |
-
{
|
| 409 |
-
"entity_table": "reviewers",
|
| 410 |
-
"kind": "forecast",
|
| 411 |
-
"name": "reviewer-churn-h4",
|
| 412 |
-
"splits": [
|
| 413 |
-
"train"
|
| 414 |
-
],
|
| 415 |
-
"target_col": "churned_h4",
|
| 416 |
-
"task_type": "binary_classification",
|
| 417 |
-
"time_col": "timestamp"
|
| 418 |
-
},
|
| 419 |
-
{
|
| 420 |
-
"entity_table": "reviewers",
|
| 421 |
-
"kind": "forecast",
|
| 422 |
-
"name": "reviewer-churn-h5",
|
| 423 |
-
"splits": [
|
| 424 |
-
"train"
|
| 425 |
-
],
|
| 426 |
-
"target_col": "churned_h5",
|
| 427 |
-
"task_type": "binary_classification",
|
| 428 |
-
"time_col": "timestamp"
|
| 429 |
-
},
|
| 430 |
-
{
|
| 431 |
-
"entity_table": "reviewers",
|
| 432 |
-
"kind": "forecast",
|
| 433 |
-
"name": "reviewer-churn-h6",
|
| 434 |
-
"splits": [
|
| 435 |
-
"train"
|
| 436 |
-
],
|
| 437 |
-
"target_col": "churned_h6",
|
| 438 |
-
"task_type": "binary_classification",
|
| 439 |
-
"time_col": "timestamp"
|
| 440 |
-
},
|
| 441 |
-
{
|
| 442 |
-
"entity_table": "reviewers",
|
| 443 |
-
"kind": "forecast",
|
| 444 |
-
"name": "reviewer-churn-h8",
|
| 445 |
-
"splits": [
|
| 446 |
-
"train"
|
| 447 |
-
],
|
| 448 |
-
"target_col": "churned_h8",
|
| 449 |
-
"task_type": "binary_classification",
|
| 450 |
-
"time_col": "timestamp"
|
| 451 |
-
},
|
| 452 |
-
{
|
| 453 |
-
"entity_table": "reviewers",
|
| 454 |
-
"kind": "forecast",
|
| 455 |
-
"name": "reviewer-distinct-products",
|
| 456 |
-
"splits": [
|
| 457 |
-
"train"
|
| 458 |
-
],
|
| 459 |
-
"target_col": "distinct_products",
|
| 460 |
-
"task_type": "regression",
|
| 461 |
-
"time_col": "timestamp"
|
| 462 |
-
},
|
| 463 |
-
{
|
| 464 |
-
"entity_table": "reviewers",
|
| 465 |
-
"kind": "forecast",
|
| 466 |
-
"name": "reviewer-harsh-critic",
|
| 467 |
-
"splits": [
|
| 468 |
-
"train"
|
| 469 |
-
],
|
| 470 |
-
"target_col": "harsh_critic",
|
| 471 |
-
"task_type": "binary_classification",
|
| 472 |
-
"time_col": "timestamp"
|
| 473 |
-
},
|
| 474 |
-
{
|
| 475 |
-
"entity_table": "reviewers",
|
| 476 |
-
"kind": "forecast",
|
| 477 |
-
"name": "reviewer-long-review-writer",
|
| 478 |
-
"splits": [
|
| 479 |
-
"train"
|
| 480 |
-
],
|
| 481 |
-
"target_col": "verbose_reviewer",
|
| 482 |
-
"task_type": "binary_classification",
|
| 483 |
-
"time_col": "timestamp"
|
| 484 |
-
},
|
| 485 |
-
{
|
| 486 |
-
"entity_table": "reviewers",
|
| 487 |
-
"kind": "forecast",
|
| 488 |
-
"name": "reviewer-long-writer",
|
| 489 |
-
"splits": [
|
| 490 |
-
"train"
|
| 491 |
-
],
|
| 492 |
-
"target_col": "long_writer",
|
| 493 |
-
"task_type": "binary_classification",
|
| 494 |
-
"time_col": "timestamp"
|
| 495 |
-
},
|
| 496 |
-
{
|
| 497 |
-
"entity_table": "reviewers",
|
| 498 |
-
"kind": "forecast",
|
| 499 |
-
"name": "reviewer-max-rating",
|
| 500 |
-
"splits": [
|
| 501 |
-
"train"
|
| 502 |
-
],
|
| 503 |
-
"target_col": "reviewer_max_rating",
|
| 504 |
-
"task_type": "regression",
|
| 505 |
-
"time_col": "timestamp"
|
| 506 |
-
},
|
| 507 |
-
{
|
| 508 |
-
"entity_table": "reviewers",
|
| 509 |
-
"kind": "forecast",
|
| 510 |
-
"name": "reviewer-max-review-len",
|
| 511 |
-
"splits": [
|
| 512 |
-
"train"
|
| 513 |
-
],
|
| 514 |
-
"target_col": "reviewer_max_len",
|
| 515 |
-
"task_type": "regression",
|
| 516 |
-
"time_col": "timestamp"
|
| 517 |
-
},
|
| 518 |
-
{
|
| 519 |
-
"entity_table": "reviewers",
|
| 520 |
-
"kind": "forecast",
|
| 521 |
-
"name": "reviewer-mean-rating",
|
| 522 |
-
"splits": [
|
| 523 |
-
"train"
|
| 524 |
-
],
|
| 525 |
-
"target_col": "pred_rating",
|
| 526 |
-
"task_type": "regression",
|
| 527 |
-
"time_col": "timestamp"
|
| 528 |
-
},
|
| 529 |
-
{
|
| 530 |
-
"entity_table": "reviewers",
|
| 531 |
-
"kind": "forecast",
|
| 532 |
-
"name": "reviewer-min-rating",
|
| 533 |
-
"splits": [
|
| 534 |
-
"train"
|
| 535 |
-
],
|
| 536 |
-
"target_col": "reviewer_min_rating",
|
| 537 |
-
"task_type": "regression",
|
| 538 |
-
"time_col": "timestamp"
|
| 539 |
-
},
|
| 540 |
-
{
|
| 541 |
-
"entity_table": "reviewers",
|
| 542 |
-
"kind": "forecast",
|
| 543 |
-
"name": "reviewer-rating-sum",
|
| 544 |
-
"splits": [
|
| 545 |
-
"train"
|
| 546 |
-
],
|
| 547 |
-
"target_col": "rating_sum",
|
| 548 |
-
"task_type": "regression",
|
| 549 |
-
"time_col": "timestamp"
|
| 550 |
-
},
|
| 551 |
-
{
|
| 552 |
-
"entity_table": "reviewers",
|
| 553 |
-
"kind": "forecast",
|
| 554 |
-
"name": "reviewer-rating-trend",
|
| 555 |
-
"splits": [
|
| 556 |
-
"train"
|
| 557 |
-
],
|
| 558 |
-
"target_col": "reviewer_rating_trend",
|
| 559 |
-
"task_type": "binary_classification",
|
| 560 |
-
"time_col": "timestamp"
|
| 561 |
-
},
|
| 562 |
-
{
|
| 563 |
-
"entity_table": "reviewers",
|
| 564 |
-
"kind": "forecast",
|
| 565 |
-
"name": "reviewer-return",
|
| 566 |
-
"splits": [
|
| 567 |
-
"train"
|
| 568 |
-
],
|
| 569 |
-
"target_col": "reviewer_returns",
|
| 570 |
-
"task_type": "binary_classification",
|
| 571 |
-
"time_col": "timestamp"
|
| 572 |
-
},
|
| 573 |
-
{
|
| 574 |
-
"entity_table": "reviewers",
|
| 575 |
-
"kind": "forecast",
|
| 576 |
-
"name": "reviewer-return-h4",
|
| 577 |
-
"splits": [
|
| 578 |
-
"train"
|
| 579 |
-
],
|
| 580 |
-
"target_col": "returned_h4",
|
| 581 |
-
"task_type": "binary_classification",
|
| 582 |
-
"time_col": "timestamp"
|
| 583 |
-
},
|
| 584 |
-
{
|
| 585 |
-
"entity_table": "reviewers",
|
| 586 |
-
"kind": "forecast",
|
| 587 |
-
"name": "reviewer-return-h5",
|
| 588 |
-
"splits": [
|
| 589 |
-
"train"
|
| 590 |
-
],
|
| 591 |
-
"target_col": "returned_h5",
|
| 592 |
-
"task_type": "binary_classification",
|
| 593 |
-
"time_col": "timestamp"
|
| 594 |
-
},
|
| 595 |
-
{
|
| 596 |
-
"entity_table": "reviewers",
|
| 597 |
-
"kind": "forecast",
|
| 598 |
-
"name": "reviewer-return-h6",
|
| 599 |
-
"splits": [
|
| 600 |
-
"train"
|
| 601 |
-
],
|
| 602 |
-
"target_col": "returned_h6",
|
| 603 |
-
"task_type": "binary_classification",
|
| 604 |
-
"time_col": "timestamp"
|
| 605 |
-
},
|
| 606 |
-
{
|
| 607 |
-
"entity_table": "reviewers",
|
| 608 |
-
"kind": "forecast",
|
| 609 |
-
"name": "reviewer-return-h8",
|
| 610 |
-
"splits": [
|
| 611 |
-
"train"
|
| 612 |
-
],
|
| 613 |
-
"target_col": "returned_h8",
|
| 614 |
-
"task_type": "binary_classification",
|
| 615 |
-
"time_col": "timestamp"
|
| 616 |
-
},
|
| 617 |
-
{
|
| 618 |
-
"entity_table": "reviewers",
|
| 619 |
-
"kind": "forecast",
|
| 620 |
-
"name": "reviewer-review-3w",
|
| 621 |
-
"splits": [
|
| 622 |
-
"train"
|
| 623 |
-
],
|
| 624 |
-
"target_col": "reviewer_3w",
|
| 625 |
-
"task_type": "regression",
|
| 626 |
-
"time_col": "timestamp"
|
| 627 |
-
},
|
| 628 |
-
{
|
| 629 |
-
"entity_table": "reviewers",
|
| 630 |
-
"kind": "forecast",
|
| 631 |
-
"name": "reviewer-review-count",
|
| 632 |
-
"splits": [
|
| 633 |
-
"train"
|
| 634 |
-
],
|
| 635 |
-
"target_col": "predict_reviewer_review_count",
|
| 636 |
-
"task_type": "regression",
|
| 637 |
-
"time_col": "timestamp"
|
| 638 |
-
},
|
| 639 |
-
{
|
| 640 |
-
"entity_table": "reviewers",
|
| 641 |
-
"kind": "forecast",
|
| 642 |
-
"name": "reviewer-time-until-next-h4",
|
| 643 |
-
"splits": [
|
| 644 |
-
"train"
|
| 645 |
-
],
|
| 646 |
-
"target_col": "days_to_next_h4",
|
| 647 |
-
"task_type": "regression",
|
| 648 |
-
"time_col": "timestamp"
|
| 649 |
-
},
|
| 650 |
-
{
|
| 651 |
-
"entity_table": "reviewers",
|
| 652 |
-
"kind": "forecast",
|
| 653 |
-
"name": "reviewer-time-until-next-h5",
|
| 654 |
-
"splits": [
|
| 655 |
-
"train"
|
| 656 |
-
],
|
| 657 |
-
"target_col": "days_to_next_h5",
|
| 658 |
-
"task_type": "regression",
|
| 659 |
-
"time_col": "timestamp"
|
| 660 |
-
},
|
| 661 |
-
{
|
| 662 |
-
"entity_table": "reviewers",
|
| 663 |
-
"kind": "forecast",
|
| 664 |
-
"name": "reviewer-time-until-next-h6",
|
| 665 |
-
"splits": [
|
| 666 |
-
"train"
|
| 667 |
-
],
|
| 668 |
-
"target_col": "days_to_next_h6",
|
| 669 |
-
"task_type": "regression",
|
| 670 |
-
"time_col": "timestamp"
|
| 671 |
-
},
|
| 672 |
-
{
|
| 673 |
-
"entity_table": "reviewers",
|
| 674 |
-
"kind": "forecast",
|
| 675 |
-
"name": "reviewer-time-until-next-h8",
|
| 676 |
-
"splits": [
|
| 677 |
-
"train"
|
| 678 |
-
],
|
| 679 |
-
"target_col": "days_to_next_h8",
|
| 680 |
-
"task_type": "regression",
|
| 681 |
-
"time_col": "timestamp"
|
| 682 |
-
},
|
| 683 |
-
{
|
| 684 |
-
"entity_table": "reviewers",
|
| 685 |
-
"kind": "forecast",
|
| 686 |
-
"name": "reviewer-verified-only",
|
| 687 |
-
"splits": [
|
| 688 |
-
"train"
|
| 689 |
-
],
|
| 690 |
-
"target_col": "all_verified_reviewer",
|
| 691 |
-
"task_type": "binary_classification",
|
| 692 |
-
"time_col": "timestamp"
|
| 693 |
-
},
|
| 694 |
-
{
|
| 695 |
-
"entity_table": "reviewers",
|
| 696 |
-
"kind": "forecast",
|
| 697 |
-
"name": "reviewer-verified-ratio",
|
| 698 |
-
"splits": [
|
| 699 |
-
"train"
|
| 700 |
-
],
|
| 701 |
-
"target_col": "pred_verified",
|
| 702 |
-
"task_type": "binary_classification",
|
| 703 |
-
"time_col": "timestamp"
|
| 704 |
-
},
|
| 705 |
-
{
|
| 706 |
-
"entity_table": "reviewers",
|
| 707 |
-
"kind": "forecast",
|
| 708 |
-
"name": "reviewer-will-review-product",
|
| 709 |
-
"splits": [
|
| 710 |
-
"train"
|
| 711 |
-
],
|
| 712 |
-
"target_col": "reviews_next",
|
| 713 |
-
"task_type": "binary_classification",
|
| 714 |
-
"time_col": "timestamp"
|
| 715 |
-
},
|
| 716 |
-
{
|
| 717 |
-
"entity_table": "reviews",
|
| 718 |
-
"kind": "autocomplete",
|
| 719 |
-
"name": "reviews-rating",
|
| 720 |
-
"splits": [],
|
| 721 |
-
"target_col": "rating",
|
| 722 |
-
"task_type": "regression",
|
| 723 |
-
"time_col": null
|
| 724 |
-
},
|
| 725 |
-
{
|
| 726 |
-
"entity_table": "reviews",
|
| 727 |
-
"kind": "autocomplete",
|
| 728 |
-
"name": "reviews-review_len",
|
| 729 |
-
"splits": [],
|
| 730 |
-
"target_col": "review_len",
|
| 731 |
-
"task_type": "regression",
|
| 732 |
-
"time_col": null
|
| 733 |
-
},
|
| 734 |
-
{
|
| 735 |
-
"entity_table": "reviews",
|
| 736 |
-
"kind": "autocomplete",
|
| 737 |
-
"name": "reviews-verified",
|
| 738 |
-
"splits": [],
|
| 739 |
-
"target_col": "verified",
|
| 740 |
-
"task_type": "binary_classification",
|
| 741 |
-
"time_col": null
|
| 742 |
-
}
|
| 743 |
-
],
|
| 744 |
-
"text_embeddings": {
|
| 745 |
-
"all-MiniLM-L12-v2": {
|
| 746 |
-
"file": "text_emb_all-MiniLM-L12-v2.bin",
|
| 747 |
-
"d_text": 384
|
| 748 |
-
}
|
| 749 |
-
}
|
| 750 |
-
}
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
join-amazon-electronics/nodes.rkyv
DELETED
|
@@ -1,3 +0,0 @@
|
|
| 1 |
-
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:c4ea8e082a17011ad5bd62e8e50a0b0a2ce18e5ca069a3d63bf394749671546a
|
| 3 |
-
size 17465859104
|
|
|
|
|
|
|
|
|
|
|
|
join-amazon-electronics/offsets.rkyv
DELETED
|
@@ -1,3 +0,0 @@
|
|
| 1 |
-
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:a01096feb8e87fd141a2f96a4cf242530e39296ea80c7d88d5eef4d7badc1ba0
|
| 3 |
-
size 551953912
|
|
|
|
|
|
|
|
|
|
|
|
join-amazon-electronics/p2f_adj.rkyv
DELETED
|
@@ -1,3 +0,0 @@
|
|
| 1 |
-
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:fc749ae3c297b0ce0682057ee1e5a9d18ce92bc8f2e934c6b96f8f054b521e26
|
| 3 |
-
size 2569725616
|
|
|
|
|
|
|
|
|
|
|
|
join-amazon-electronics/table_info.json
DELETED
|
@@ -1 +0,0 @@
|
|
| 1 |
-
{"product-rating-trend:Train":{"node_idx_offset":18278950,"num_nodes":547713},"reviewers:Db":{"node_idx_offset":160052,"num_nodes":540625},"reviewer-review-count:Train":{"node_idx_offset":56719441,"num_nodes":3769577},"reviewer-return-h8:Train":{"node_idx_offset":52180464,"num_nodes":449274},"product-churn-h4:Train":{"node_idx_offset":10525214,"num_nodes":838086},"reviews:Db":{"node_idx_offset":700677,"num_nodes":4997332},"reviewer-churn-h4:Train":{"node_idx_offset":32934550,"num_nodes":2699794},"reviewer-time-until-next-h6:Train":{"node_idx_offset":62514140,"num_nodes":751351},"reviewer-time-until-next-h8:Train":{"node_idx_offset":63265491,"num_nodes":778450},"reviewer-long-review-writer:Train":{"node_idx_offset":42634312,"num_nodes":590319},"reviewer-return-h6:Train":{"node_idx_offset":51567906,"num_nodes":612558},"product-time-until-next-h6:Train":{"node_idx_offset":22563741,"num_nodes":323986},"reviewer-max-rating:Train":{"node_idx_offset":43814950,"num_nodes":590319},"product-verified-count:Train":{"node_idx_offset":25418015,"num_nodes":745705},"product-low-rating-event:Train":{"node_idx_offset":13794046,"num_nodes":745705},"reviewer-time-until-next-h5:Train":{"node_idx_offset":61456756,"num_nodes":1057384},"reviewer-return:Train":{"node_idx_offset":47061900,"num_nodes":2214396},"reviewer-distinct-products:Train":{"node_idx_offset":41453674,"num_nodes":590319},"reviewer-avg-review-length:Train":{"node_idx_offset":28574654,"num_nodes":590319},"reviewer-will-review-product:Train":{"node_idx_offset":65224579,"num_nodes":3769657},"product-low-rating:Train":{"node_idx_offset":13048341,"num_nodes":745705},"product-return-h4:Train":{"node_idx_offset":19921630,"num_nodes":235402},"reviewer-churn-h8:Train":{"node_idx_offset":39949748,"num_nodes":1503926},"product-review-length-change:Train":{"node_idx_offset":22016028,"num_nodes":547713},"product-avg-review-length:Train":{"node_idx_offset":8108943,"num_nodes":751042},"reviewer-verified-only:Train":{"node_idx_offset":64043941,"num_nodes":590319},"product-will-be-reviewed:Train":{"node_idx_offset":26909425,"num_nodes":1665229},"product-return-h8:Train":{"node_idx_offset":20268870,"num_nodes":81929},"product-max-review-length:Train":{"node_idx_offset":15290793,"num_nodes":751042},"product-any-new-review:Train":{"node_idx_offset":6443714,"num_nodes":1665229},"reviewer-long-writer:Train":{"node_idx_offset":43224631,"num_nodes":590319},"product-time-until-next-h8:Train":{"node_idx_offset":22887727,"num_nodes":293175},"reviewer-return-h5:Train":{"node_idx_offset":50481900,"num_nodes":1086006},"product-return-h6:Train":{"node_idx_offset":20157032,"num_nodes":111838},"product-all-verified:Train":{"node_idx_offset":5698009,"num_nodes":745705},"reviewer-churn-h5:Train":{"node_idx_offset":35634344,"num_nodes":2631901},"product-rating-volatility:Train":{"node_idx_offset":18826663,"num_nodes":407885},"reviewer-min-rating:Train":{"node_idx_offset":45585907,"num_nodes":590319},"product-popular-next-window:Train":{"node_idx_offset":17533245,"num_nodes":745705},"product-churn-h8:Train":{"node_idx_offset":11864123,"num_nodes":438513},"product-min-rating:Train":{"node_idx_offset":16787540,"num_nodes":745705},"reviewer-time-until-next-h4:Train":{"node_idx_offset":60489018,"num_nodes":967738},"product-mean-rating:Train":{"node_idx_offset":16041835,"num_nodes":745705},"product-max-review-len:Train":{"node_idx_offset":14539751,"num_nodes":751042},"product-top-review-volume:Train":{"node_idx_offset":23180902,"num_nodes":745703},"reviewer-return-h4:Train":{"node_idx_offset":49276296,"num_nodes":1205604},"products:Db":{"node_idx_offset":0,"num_nodes":160052},"product-unique-reviewers:Train":{"node_idx_offset":24672310,"num_nodes":745705},"product-verified-share:Train":{"node_idx_offset":26163720,"num_nodes":745705},"reviewer-churn:Train":{"node_idx_offset":29164973,"num_nodes":3769577},"reviewer-verified-ratio:Train":{"node_idx_offset":64634260,"num_nodes":590319},"product-churn-h6:Train":{"node_idx_offset":11363300,"num_nodes":500823},"reviewer-review-3w:Train":{"node_idx_offset":52629738,"num_nodes":4089703},"reviewer-rating-trend:Train":{"node_idx_offset":46766545,"num_nodes":295355},"reviewer-rating-sum:Train":{"node_idx_offset":46176226,"num_nodes":590319},"reviewer-churn-h6:Train":{"node_idx_offset":38266245,"num_nodes":1683503},"product-long-review:Train":{"node_idx_offset":12302636,"num_nodes":745705},"reviewer-max-review-len:Train":{"node_idx_offset":44405269,"num_nodes":590319},"reviewer-mean-rating:Train":{"node_idx_offset":44995588,"num_nodes":590319},"product-total-rating-sum:Train":{"node_idx_offset":23926605,"num_nodes":745705},"reviewer-harsh-critic:Train":{"node_idx_offset":42043993,"num_nodes":590319},"product-return:Train":{"node_idx_offset":19234548,"num_nodes":687082},"product-churn:Train":{"node_idx_offset":8859985,"num_nodes":1665229},"product-review-count:Train":{"node_idx_offset":20350799,"num_nodes":1665229}}
|
|
|
|
|
|
join-amazon-electronics/text.json
DELETED
|
@@ -1,3 +0,0 @@
|
|
| 1 |
-
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:97c18c58103ae787a00fa139e4f6673f666fcffa6fdf3318bc5884ff3e134b91
|
| 3 |
-
size 14710130
|
|
|
|
|
|
|
|
|
|
|
|
join-amazon-electronics/text_emb_all-MiniLM-L12-v2.bin
DELETED
|
@@ -1,3 +0,0 @@
|
|
| 1 |
-
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:912930befb4eb379695db3a1bb92f8e57bf8330224ba3a758b9736634ba5a214
|
| 3 |
-
size 379405824
|
|
|
|
|
|
|
|
|
|
|
|
join-amazon-fashion/column_index.json
DELETED
|
@@ -1 +0,0 @@
|
|
| 1 |
-
{"timestamp of reviewer-verified-only":745109,"timestamp of reviewer-time-until-next-8x":745639,"predict_reviewer_churn of reviewer-churn":745101,"pred_verified of reviewer-verified-ratio":745634,"verified_rate of product-verified-share":745132,"reviewer_id of reviewer-time-until-next-8x":745637,"popular of product-popular-next-window":745650,"reviewer_min_rating of reviewer-min-rating":745104,"asin of product-review-concentration":745673,"timestamp of reviewer-return":745678,"rating_trend of product-rating-trend":745690,"verified_count of product-verified-count":20,"timestamp of product-rating-change":745081,"reviewer_id of reviewer-return-4x":745063,"reviewer_id of reviewer-harsh-critic":745071,"timestamp of product-reviewer-min-id":745121,"timestamp of reviewer-return-7x":745076,"timestamp of product-churn-6x":745662,"reviewer_id of reviewer-rating-sum":745609,"reviewer_id of reviewer-max-rating":745139,"timestamp of reviewer-return-4x":745064,"asin of product-reviewer-min-id":745119,"all_verified of product-all-verified":745128,"timestamp of product-will-be-reviewed":745658,"reviews_next of reviewer-will-review-fashion":745655,"asin of product-return":27,"reviewer_id of reviewer-verified-ratio":745633,"asin of product-mean-rating":745681,"churned_6x of reviewer-churn-6x":4,"days_until_next_product_review_6x of product-time-until-next-6x":36,"timestamp of reviewer-max-rating":745141,"reviewer_id of reviewer-churn-5x":745621,"avg_rating of products":383088,"predict_reviewer_review_count of reviewer-review-count":745646,"timestamp of product-return-6x":745666,"top_activity of reviewer-top-activity":12,"reviewer_range of product-unique-reviewers":745092,"timestamp of product-low-rating":745061,"days_until_next_product_review_4x of product-time-until-next-4x":745088,"reviewer_id of reviewer-time-until-next-6x":745625,"timestamp of reviewer-harsh-critic":745073,"asin of product-verified-share":745131,"reviewer_id of reviewer-return-5x":745641,"min_rating of product-min-rating":383092,"predict_product_churn of product-churn":745671,"product_churned_8x of product-churn-8x":745615,"timestamp of product-rating-trend":745691,"rating_sum of reviewer-rating-sum":745610,"asin of product-churn":745669,"timestamp of product-all-verified":745129,"timestamp of product-time-until-next-6x":37,"vote of reviews":745152,"timestamp of reviewer-rating-sum":745611,"timestamp of reviewer-review-count":745647,"timestamp of product-any-new-review":745068,"timestamp of reviewer-return-6x":745112,"asin of product-rating-trend":745689,"asin of products":54,"reviewed_next of product-will-be-reviewed":745659,"asin of product-unique-reviewers":745091,"asin of product-churn-4x":31,"title of products":55,"reviewer_returns_5x of reviewer-return-5x":745643,"asin of product-mean-reviewer-id":6,"harsh_critic of reviewer-harsh-critic":745072,"timestamp of reviewer-churn-4x":44,"timestamp of product-time-until-next-4x":745089,"identifier of reviews":745607,"reviewer_3w of reviewer-review-3w":745056,"timestamp of reviewer-time-until-next-4x":53,"timestamp of reviewer-mean-rating":745145,"timestamp of product-churn":745670,"reviewer_id of reviewer-generous":745135,"review_concentration of product-review-concentration":745674,"asin of product-max-rating":745685,"reviewer_returns_6x of reviewer-return-6x":745113,"timestamp of product-review-count":49,"low_rating of product-low-rating":745060,"product_3w of product-review-count-3w":383096,"churned_8x of reviewer-churn-8x":745125,"timestamp of product-verified-count":21,"product_returns of product-return":29,"timestamp of product-top-review-volume":745117,"book_has_review of product-any-new-review":745069,"days_until_next_review_5x of reviewer-time-until-next-5x":24,"reviewer_returns_8x of reviewer-return-8x":745619,"predict_product_review_count of product-review-count":48,"timestamp of reviewer-churn":745100,"min_reviewer_id of product-reviewer-min-id":745120,"reviewer_id of reviewer-top-activity":11,"timestamp of reviewer-verified-ratio":745635,"asin of product-will-be-reviewed":745657,"reviewer_id of reviewer-will-review-fashion":745653,"reviewer_id of reviewer-churn-6x":1,"reviewer_id of reviewer-distinct-products":745629,"timestamp of product-return":28,"timestamp of product-mean-reviewer-id":9,"days_until_next_review_6x of reviewer-time-until-next-6x":745626,"reviewer_id of reviewer-return-7x":745075,"timestamp of product-review-count-3w":383097,"rating_volatility of product-rating-volatility":745084,"days_until_next_review_4x of reviewer-time-until-next-4x":52,"category of products":383086,"asin of product-review-count-3w":383095,"timestamp of product-rating-volatility":745085,"reviewer_id of reviewer-churn":745099,"asin of product-popular-next-window":745649,"asin of product-return-6x":745665,"timestamp of product-review-concentration":745675,"top_review_volume of product-top-review-volume":745116,"product_churned_6x of product-churn-6x":745663,"n_reviews of products":383089,"all_verified_reviewer of reviewer-verified-only":745108,"reviewer_id of reviewer-review-3w":745055,"reviewer_id of reviewer-churn-8x":745123,"asin of reviews":745148,"timestamp of product-min-rating":383093,"pred_rating of reviewer-mean-rating":745144,"timestamp of product-return-4x":40,"max_rating of product-max-rating":745686,"timestamp of reviewer-top-activity":13,"timestamp of product-churn-8x":745614,"timestamp of product-mean-rating":745683,"timestamp of reviewer-churn-6x":3,"max_rating of reviewer-max-rating":745140,"reviewer_id of reviewer-time-until-next-5x":23,"reviewer_returns_7x of reviewer-return-7x":745077,"asin of product-low-rating-event":745095,"timestamp of product-churn-4x":32,"timestamp of reviewer-churn-8x":745124,"reviewer_id of reviews":745147,"rating_sum of product-total-rating-sum":16,"reviewer_name of reviewers":383099,"timestamp of reviewer-return-8x":745618,"product_returns_6x of product-return-6x":745667,"reviewer_returns of reviewer-return":745679,"timestamp of product-max-rating":745687,"asin of product-time-until-next-6x":35,"brand of products":356466,"reviewer_id of reviewer-return":745677,"asin of product-churn-6x":745661,"asin of product-review-count":47,"timestamp of reviews":745150,"days_until_next_review_8x of reviewer-time-until-next-8x":745638,"timestamp of product-total-rating-sum":17,"reviewer_id of reviewer-churn-4x":43,"timestamp of product-unique-reviewers":745093,"timestamp of reviewer-time-until-next-5x":25,"churned_4x of reviewer-churn-4x":45,"rating_change of product-rating-change":745080,"timestamp of product-verified-share":745133,"asin of product-rating-change":745079,"timestamp of reviewer-generous":745137,"reviewer_returns_4x of reviewer-return-4x":745065,"verified of reviews":745151,"timestamp of reviewer-will-review-fashion":745654,"mean_reviewer_id of product-mean-reviewer-id":8,"timestamp of reviewer-churn-5x":745622,"asin of product-rating-volatility":745083,"asin of product-top-review-volume":745115,"asin of product-churn-8x":745613,"reviewer_id of reviewer-min-rating":745103,"asin of product-min-rating":383091,"reviewer_id of reviewer-return-6x":745111,"low_rating_event of product-low-rating-event":745096,"pred_rating of product-mean-rating":745682,"asin of product-low-rating":745059,"asin of product-return-4x":39,"timestamp of reviewer-min-rating":745105,"distinct_products of reviewer-distinct-products":745630,"asin of product-total-rating-sum":15,"timestamp of reviewer-return-5x":745642,"asin of product-time-until-next-4x":745087,"reviewer_id of reviewer-mean-rating":745143,"product_returns_4x of product-return-4x":41,"asin of product-verified-count":19,"churned_5x of reviewer-churn-5x":745623,"reviewer_id of reviewer-review-count":745645,"timestamp of reviewer-time-until-next-6x":745627,"timestamp of product-low-rating-event":745097,"reviewer_id of reviewer-time-until-next-4x":51,"timestamp of reviewer-review-3w":745057,"asin of product-any-new-review":745067,"rating of reviews":745149,"reviewer_id of reviewer-return-8x":745617,"timestamp of product-popular-next-window":745651,"reviewer_id of reviewers":383098,"generous of reviewer-generous":745136,"asin of product-all-verified":745127,"timestamp of reviewer-distinct-products":745631,"product_churned_4x of product-churn-4x":33,"reviewer_id of reviewer-verified-only":745107}
|
|
|
|
|
|
join-amazon-fashion/meta.json
DELETED
|
@@ -1,710 +0,0 @@
|
|
| 1 |
-
{
|
| 2 |
-
"files": {
|
| 3 |
-
"column_index": "column_index.json",
|
| 4 |
-
"nodes": "nodes.rkyv",
|
| 5 |
-
"offsets": "offsets.rkyv",
|
| 6 |
-
"p2f_adj": "p2f_adj.rkyv",
|
| 7 |
-
"table_info": "table_info.json",
|
| 8 |
-
"text": "text.json"
|
| 9 |
-
},
|
| 10 |
-
"format_version": 1,
|
| 11 |
-
"name": "join-amazon-fashion",
|
| 12 |
-
"num_db_tables": 3,
|
| 13 |
-
"num_nodes": 85350291,
|
| 14 |
-
"num_task_tables": 59,
|
| 15 |
-
"num_text_strings": 745692,
|
| 16 |
-
"source": "stanford-star/the-join/join-amazon-fashion",
|
| 17 |
-
"tasks": [
|
| 18 |
-
{
|
| 19 |
-
"entity_table": "products",
|
| 20 |
-
"kind": "forecast",
|
| 21 |
-
"name": "product-all-verified",
|
| 22 |
-
"splits": [
|
| 23 |
-
"train"
|
| 24 |
-
],
|
| 25 |
-
"target_col": "all_verified",
|
| 26 |
-
"task_type": "binary_classification",
|
| 27 |
-
"time_col": "timestamp"
|
| 28 |
-
},
|
| 29 |
-
{
|
| 30 |
-
"entity_table": "products",
|
| 31 |
-
"kind": "forecast",
|
| 32 |
-
"name": "product-any-new-review",
|
| 33 |
-
"splits": [
|
| 34 |
-
"train"
|
| 35 |
-
],
|
| 36 |
-
"target_col": "book_has_review",
|
| 37 |
-
"task_type": "binary_classification",
|
| 38 |
-
"time_col": "timestamp"
|
| 39 |
-
},
|
| 40 |
-
{
|
| 41 |
-
"entity_table": "products",
|
| 42 |
-
"kind": "forecast",
|
| 43 |
-
"name": "product-churn",
|
| 44 |
-
"splits": [
|
| 45 |
-
"train"
|
| 46 |
-
],
|
| 47 |
-
"target_col": "predict_product_churn",
|
| 48 |
-
"task_type": "binary_classification",
|
| 49 |
-
"time_col": "timestamp"
|
| 50 |
-
},
|
| 51 |
-
{
|
| 52 |
-
"entity_table": "products",
|
| 53 |
-
"kind": "forecast",
|
| 54 |
-
"name": "product-churn-4x",
|
| 55 |
-
"splits": [
|
| 56 |
-
"train"
|
| 57 |
-
],
|
| 58 |
-
"target_col": "product_churned_4x",
|
| 59 |
-
"task_type": "binary_classification",
|
| 60 |
-
"time_col": "timestamp"
|
| 61 |
-
},
|
| 62 |
-
{
|
| 63 |
-
"entity_table": "products",
|
| 64 |
-
"kind": "forecast",
|
| 65 |
-
"name": "product-churn-6x",
|
| 66 |
-
"splits": [
|
| 67 |
-
"train"
|
| 68 |
-
],
|
| 69 |
-
"target_col": "product_churned_6x",
|
| 70 |
-
"task_type": "binary_classification",
|
| 71 |
-
"time_col": "timestamp"
|
| 72 |
-
},
|
| 73 |
-
{
|
| 74 |
-
"entity_table": "products",
|
| 75 |
-
"kind": "forecast",
|
| 76 |
-
"name": "product-churn-8x",
|
| 77 |
-
"splits": [
|
| 78 |
-
"train"
|
| 79 |
-
],
|
| 80 |
-
"target_col": "product_churned_8x",
|
| 81 |
-
"task_type": "binary_classification",
|
| 82 |
-
"time_col": "timestamp"
|
| 83 |
-
},
|
| 84 |
-
{
|
| 85 |
-
"entity_table": "products",
|
| 86 |
-
"kind": "forecast",
|
| 87 |
-
"name": "product-low-rating",
|
| 88 |
-
"splits": [
|
| 89 |
-
"train"
|
| 90 |
-
],
|
| 91 |
-
"target_col": "low_rating",
|
| 92 |
-
"task_type": "binary_classification",
|
| 93 |
-
"time_col": "timestamp"
|
| 94 |
-
},
|
| 95 |
-
{
|
| 96 |
-
"entity_table": "products",
|
| 97 |
-
"kind": "forecast",
|
| 98 |
-
"name": "product-low-rating-event",
|
| 99 |
-
"splits": [
|
| 100 |
-
"train"
|
| 101 |
-
],
|
| 102 |
-
"target_col": "low_rating_event",
|
| 103 |
-
"task_type": "binary_classification",
|
| 104 |
-
"time_col": "timestamp"
|
| 105 |
-
},
|
| 106 |
-
{
|
| 107 |
-
"entity_table": "products",
|
| 108 |
-
"kind": "forecast",
|
| 109 |
-
"name": "product-max-rating",
|
| 110 |
-
"splits": [
|
| 111 |
-
"train"
|
| 112 |
-
],
|
| 113 |
-
"target_col": "max_rating",
|
| 114 |
-
"task_type": "regression",
|
| 115 |
-
"time_col": "timestamp"
|
| 116 |
-
},
|
| 117 |
-
{
|
| 118 |
-
"entity_table": "products",
|
| 119 |
-
"kind": "forecast",
|
| 120 |
-
"name": "product-mean-rating",
|
| 121 |
-
"splits": [
|
| 122 |
-
"train"
|
| 123 |
-
],
|
| 124 |
-
"target_col": "pred_rating",
|
| 125 |
-
"task_type": "regression",
|
| 126 |
-
"time_col": "timestamp"
|
| 127 |
-
},
|
| 128 |
-
{
|
| 129 |
-
"entity_table": "products",
|
| 130 |
-
"kind": "forecast",
|
| 131 |
-
"name": "product-mean-reviewer-id",
|
| 132 |
-
"splits": [
|
| 133 |
-
"train"
|
| 134 |
-
],
|
| 135 |
-
"target_col": "mean_reviewer_id",
|
| 136 |
-
"task_type": "regression",
|
| 137 |
-
"time_col": "timestamp"
|
| 138 |
-
},
|
| 139 |
-
{
|
| 140 |
-
"entity_table": "products",
|
| 141 |
-
"kind": "forecast",
|
| 142 |
-
"name": "product-min-rating",
|
| 143 |
-
"splits": [
|
| 144 |
-
"train"
|
| 145 |
-
],
|
| 146 |
-
"target_col": "min_rating",
|
| 147 |
-
"task_type": "regression",
|
| 148 |
-
"time_col": "timestamp"
|
| 149 |
-
},
|
| 150 |
-
{
|
| 151 |
-
"entity_table": "products",
|
| 152 |
-
"kind": "forecast",
|
| 153 |
-
"name": "product-popular-next-window",
|
| 154 |
-
"splits": [
|
| 155 |
-
"train"
|
| 156 |
-
],
|
| 157 |
-
"target_col": "popular",
|
| 158 |
-
"task_type": "binary_classification",
|
| 159 |
-
"time_col": "timestamp"
|
| 160 |
-
},
|
| 161 |
-
{
|
| 162 |
-
"entity_table": "products",
|
| 163 |
-
"kind": "forecast",
|
| 164 |
-
"name": "product-rating-change",
|
| 165 |
-
"splits": [
|
| 166 |
-
"train"
|
| 167 |
-
],
|
| 168 |
-
"target_col": "rating_change",
|
| 169 |
-
"task_type": "regression",
|
| 170 |
-
"time_col": "timestamp"
|
| 171 |
-
},
|
| 172 |
-
{
|
| 173 |
-
"entity_table": "products",
|
| 174 |
-
"kind": "forecast",
|
| 175 |
-
"name": "product-rating-trend",
|
| 176 |
-
"splits": [
|
| 177 |
-
"train"
|
| 178 |
-
],
|
| 179 |
-
"target_col": "rating_trend",
|
| 180 |
-
"task_type": "binary_classification",
|
| 181 |
-
"time_col": "timestamp"
|
| 182 |
-
},
|
| 183 |
-
{
|
| 184 |
-
"entity_table": "products",
|
| 185 |
-
"kind": "forecast",
|
| 186 |
-
"name": "product-rating-volatility",
|
| 187 |
-
"splits": [
|
| 188 |
-
"train"
|
| 189 |
-
],
|
| 190 |
-
"target_col": "rating_volatility",
|
| 191 |
-
"task_type": "regression",
|
| 192 |
-
"time_col": "timestamp"
|
| 193 |
-
},
|
| 194 |
-
{
|
| 195 |
-
"entity_table": "products",
|
| 196 |
-
"kind": "forecast",
|
| 197 |
-
"name": "product-return",
|
| 198 |
-
"splits": [
|
| 199 |
-
"train"
|
| 200 |
-
],
|
| 201 |
-
"target_col": "product_returns",
|
| 202 |
-
"task_type": "binary_classification",
|
| 203 |
-
"time_col": "timestamp"
|
| 204 |
-
},
|
| 205 |
-
{
|
| 206 |
-
"entity_table": "products",
|
| 207 |
-
"kind": "forecast",
|
| 208 |
-
"name": "product-return-4x",
|
| 209 |
-
"splits": [
|
| 210 |
-
"train"
|
| 211 |
-
],
|
| 212 |
-
"target_col": "product_returns_4x",
|
| 213 |
-
"task_type": "binary_classification",
|
| 214 |
-
"time_col": "timestamp"
|
| 215 |
-
},
|
| 216 |
-
{
|
| 217 |
-
"entity_table": "products",
|
| 218 |
-
"kind": "forecast",
|
| 219 |
-
"name": "product-return-6x",
|
| 220 |
-
"splits": [
|
| 221 |
-
"train"
|
| 222 |
-
],
|
| 223 |
-
"target_col": "product_returns_6x",
|
| 224 |
-
"task_type": "binary_classification",
|
| 225 |
-
"time_col": "timestamp"
|
| 226 |
-
},
|
| 227 |
-
{
|
| 228 |
-
"entity_table": "products",
|
| 229 |
-
"kind": "forecast",
|
| 230 |
-
"name": "product-review-concentration",
|
| 231 |
-
"splits": [
|
| 232 |
-
"train"
|
| 233 |
-
],
|
| 234 |
-
"target_col": "review_concentration",
|
| 235 |
-
"task_type": "regression",
|
| 236 |
-
"time_col": "timestamp"
|
| 237 |
-
},
|
| 238 |
-
{
|
| 239 |
-
"entity_table": "products",
|
| 240 |
-
"kind": "forecast",
|
| 241 |
-
"name": "product-review-count",
|
| 242 |
-
"splits": [
|
| 243 |
-
"train"
|
| 244 |
-
],
|
| 245 |
-
"target_col": "predict_product_review_count",
|
| 246 |
-
"task_type": "regression",
|
| 247 |
-
"time_col": "timestamp"
|
| 248 |
-
},
|
| 249 |
-
{
|
| 250 |
-
"entity_table": "products",
|
| 251 |
-
"kind": "forecast",
|
| 252 |
-
"name": "product-review-count-3w",
|
| 253 |
-
"splits": [
|
| 254 |
-
"train"
|
| 255 |
-
],
|
| 256 |
-
"target_col": "product_3w",
|
| 257 |
-
"task_type": "regression",
|
| 258 |
-
"time_col": "timestamp"
|
| 259 |
-
},
|
| 260 |
-
{
|
| 261 |
-
"entity_table": "products",
|
| 262 |
-
"kind": "forecast",
|
| 263 |
-
"name": "product-reviewer-min-id",
|
| 264 |
-
"splits": [
|
| 265 |
-
"train"
|
| 266 |
-
],
|
| 267 |
-
"target_col": "min_reviewer_id",
|
| 268 |
-
"task_type": "regression",
|
| 269 |
-
"time_col": "timestamp"
|
| 270 |
-
},
|
| 271 |
-
{
|
| 272 |
-
"entity_table": "products",
|
| 273 |
-
"kind": "forecast",
|
| 274 |
-
"name": "product-time-until-next-4x",
|
| 275 |
-
"splits": [
|
| 276 |
-
"train"
|
| 277 |
-
],
|
| 278 |
-
"target_col": "days_until_next_product_review_4x",
|
| 279 |
-
"task_type": "regression",
|
| 280 |
-
"time_col": "timestamp"
|
| 281 |
-
},
|
| 282 |
-
{
|
| 283 |
-
"entity_table": "products",
|
| 284 |
-
"kind": "forecast",
|
| 285 |
-
"name": "product-time-until-next-6x",
|
| 286 |
-
"splits": [
|
| 287 |
-
"train"
|
| 288 |
-
],
|
| 289 |
-
"target_col": "days_until_next_product_review_6x",
|
| 290 |
-
"task_type": "regression",
|
| 291 |
-
"time_col": "timestamp"
|
| 292 |
-
},
|
| 293 |
-
{
|
| 294 |
-
"entity_table": "products",
|
| 295 |
-
"kind": "forecast",
|
| 296 |
-
"name": "product-top-review-volume",
|
| 297 |
-
"splits": [
|
| 298 |
-
"train"
|
| 299 |
-
],
|
| 300 |
-
"target_col": "top_review_volume",
|
| 301 |
-
"task_type": "binary_classification",
|
| 302 |
-
"time_col": "timestamp"
|
| 303 |
-
},
|
| 304 |
-
{
|
| 305 |
-
"entity_table": "products",
|
| 306 |
-
"kind": "forecast",
|
| 307 |
-
"name": "product-total-rating-sum",
|
| 308 |
-
"splits": [
|
| 309 |
-
"train"
|
| 310 |
-
],
|
| 311 |
-
"target_col": "rating_sum",
|
| 312 |
-
"task_type": "regression",
|
| 313 |
-
"time_col": "timestamp"
|
| 314 |
-
},
|
| 315 |
-
{
|
| 316 |
-
"entity_table": "products",
|
| 317 |
-
"kind": "forecast",
|
| 318 |
-
"name": "product-unique-reviewers",
|
| 319 |
-
"splits": [
|
| 320 |
-
"train"
|
| 321 |
-
],
|
| 322 |
-
"target_col": "reviewer_range",
|
| 323 |
-
"task_type": "regression",
|
| 324 |
-
"time_col": "timestamp"
|
| 325 |
-
},
|
| 326 |
-
{
|
| 327 |
-
"entity_table": "products",
|
| 328 |
-
"kind": "forecast",
|
| 329 |
-
"name": "product-verified-count",
|
| 330 |
-
"splits": [
|
| 331 |
-
"train"
|
| 332 |
-
],
|
| 333 |
-
"target_col": "verified_count",
|
| 334 |
-
"task_type": "regression",
|
| 335 |
-
"time_col": "timestamp"
|
| 336 |
-
},
|
| 337 |
-
{
|
| 338 |
-
"entity_table": "products",
|
| 339 |
-
"kind": "forecast",
|
| 340 |
-
"name": "product-verified-share",
|
| 341 |
-
"splits": [
|
| 342 |
-
"train"
|
| 343 |
-
],
|
| 344 |
-
"target_col": "verified_rate",
|
| 345 |
-
"task_type": "regression",
|
| 346 |
-
"time_col": "timestamp"
|
| 347 |
-
},
|
| 348 |
-
{
|
| 349 |
-
"entity_table": "products",
|
| 350 |
-
"kind": "forecast",
|
| 351 |
-
"name": "product-will-be-reviewed",
|
| 352 |
-
"splits": [
|
| 353 |
-
"train"
|
| 354 |
-
],
|
| 355 |
-
"target_col": "reviewed_next",
|
| 356 |
-
"task_type": "binary_classification",
|
| 357 |
-
"time_col": "timestamp"
|
| 358 |
-
},
|
| 359 |
-
{
|
| 360 |
-
"entity_table": "products",
|
| 361 |
-
"kind": "autocomplete",
|
| 362 |
-
"name": "products-avg_rating",
|
| 363 |
-
"splits": [],
|
| 364 |
-
"target_col": "avg_rating",
|
| 365 |
-
"task_type": "regression",
|
| 366 |
-
"time_col": null
|
| 367 |
-
},
|
| 368 |
-
{
|
| 369 |
-
"entity_table": "products",
|
| 370 |
-
"kind": "autocomplete",
|
| 371 |
-
"name": "products-n_reviews",
|
| 372 |
-
"splits": [],
|
| 373 |
-
"target_col": "n_reviews",
|
| 374 |
-
"task_type": "regression",
|
| 375 |
-
"time_col": null
|
| 376 |
-
},
|
| 377 |
-
{
|
| 378 |
-
"entity_table": "reviewers",
|
| 379 |
-
"kind": "forecast",
|
| 380 |
-
"name": "reviewer-churn",
|
| 381 |
-
"splits": [
|
| 382 |
-
"train"
|
| 383 |
-
],
|
| 384 |
-
"target_col": "predict_reviewer_churn",
|
| 385 |
-
"task_type": "binary_classification",
|
| 386 |
-
"time_col": "timestamp"
|
| 387 |
-
},
|
| 388 |
-
{
|
| 389 |
-
"entity_table": "reviewers",
|
| 390 |
-
"kind": "forecast",
|
| 391 |
-
"name": "reviewer-churn-4x",
|
| 392 |
-
"splits": [
|
| 393 |
-
"train"
|
| 394 |
-
],
|
| 395 |
-
"target_col": "churned_4x",
|
| 396 |
-
"task_type": "binary_classification",
|
| 397 |
-
"time_col": "timestamp"
|
| 398 |
-
},
|
| 399 |
-
{
|
| 400 |
-
"entity_table": "reviewers",
|
| 401 |
-
"kind": "forecast",
|
| 402 |
-
"name": "reviewer-churn-5x",
|
| 403 |
-
"splits": [
|
| 404 |
-
"train"
|
| 405 |
-
],
|
| 406 |
-
"target_col": "churned_5x",
|
| 407 |
-
"task_type": "binary_classification",
|
| 408 |
-
"time_col": "timestamp"
|
| 409 |
-
},
|
| 410 |
-
{
|
| 411 |
-
"entity_table": "reviewers",
|
| 412 |
-
"kind": "forecast",
|
| 413 |
-
"name": "reviewer-churn-6x",
|
| 414 |
-
"splits": [
|
| 415 |
-
"train"
|
| 416 |
-
],
|
| 417 |
-
"target_col": "churned_6x",
|
| 418 |
-
"task_type": "binary_classification",
|
| 419 |
-
"time_col": "timestamp"
|
| 420 |
-
},
|
| 421 |
-
{
|
| 422 |
-
"entity_table": "reviewers",
|
| 423 |
-
"kind": "forecast",
|
| 424 |
-
"name": "reviewer-churn-8x",
|
| 425 |
-
"splits": [
|
| 426 |
-
"train"
|
| 427 |
-
],
|
| 428 |
-
"target_col": "churned_8x",
|
| 429 |
-
"task_type": "binary_classification",
|
| 430 |
-
"time_col": "timestamp"
|
| 431 |
-
},
|
| 432 |
-
{
|
| 433 |
-
"entity_table": "reviewers",
|
| 434 |
-
"kind": "forecast",
|
| 435 |
-
"name": "reviewer-distinct-products",
|
| 436 |
-
"splits": [
|
| 437 |
-
"train"
|
| 438 |
-
],
|
| 439 |
-
"target_col": "distinct_products",
|
| 440 |
-
"task_type": "regression",
|
| 441 |
-
"time_col": "timestamp"
|
| 442 |
-
},
|
| 443 |
-
{
|
| 444 |
-
"entity_table": "reviewers",
|
| 445 |
-
"kind": "forecast",
|
| 446 |
-
"name": "reviewer-generous",
|
| 447 |
-
"splits": [
|
| 448 |
-
"train"
|
| 449 |
-
],
|
| 450 |
-
"target_col": "generous",
|
| 451 |
-
"task_type": "binary_classification",
|
| 452 |
-
"time_col": "timestamp"
|
| 453 |
-
},
|
| 454 |
-
{
|
| 455 |
-
"entity_table": "reviewers",
|
| 456 |
-
"kind": "forecast",
|
| 457 |
-
"name": "reviewer-harsh-critic",
|
| 458 |
-
"splits": [
|
| 459 |
-
"train"
|
| 460 |
-
],
|
| 461 |
-
"target_col": "harsh_critic",
|
| 462 |
-
"task_type": "binary_classification",
|
| 463 |
-
"time_col": "timestamp"
|
| 464 |
-
},
|
| 465 |
-
{
|
| 466 |
-
"entity_table": "reviewers",
|
| 467 |
-
"kind": "forecast",
|
| 468 |
-
"name": "reviewer-max-rating",
|
| 469 |
-
"splits": [
|
| 470 |
-
"train"
|
| 471 |
-
],
|
| 472 |
-
"target_col": "max_rating",
|
| 473 |
-
"task_type": "regression",
|
| 474 |
-
"time_col": "timestamp"
|
| 475 |
-
},
|
| 476 |
-
{
|
| 477 |
-
"entity_table": "reviewers",
|
| 478 |
-
"kind": "forecast",
|
| 479 |
-
"name": "reviewer-mean-rating",
|
| 480 |
-
"splits": [
|
| 481 |
-
"train"
|
| 482 |
-
],
|
| 483 |
-
"target_col": "pred_rating",
|
| 484 |
-
"task_type": "regression",
|
| 485 |
-
"time_col": "timestamp"
|
| 486 |
-
},
|
| 487 |
-
{
|
| 488 |
-
"entity_table": "reviewers",
|
| 489 |
-
"kind": "forecast",
|
| 490 |
-
"name": "reviewer-min-rating",
|
| 491 |
-
"splits": [
|
| 492 |
-
"train"
|
| 493 |
-
],
|
| 494 |
-
"target_col": "reviewer_min_rating",
|
| 495 |
-
"task_type": "regression",
|
| 496 |
-
"time_col": "timestamp"
|
| 497 |
-
},
|
| 498 |
-
{
|
| 499 |
-
"entity_table": "reviewers",
|
| 500 |
-
"kind": "forecast",
|
| 501 |
-
"name": "reviewer-rating-sum",
|
| 502 |
-
"splits": [
|
| 503 |
-
"train"
|
| 504 |
-
],
|
| 505 |
-
"target_col": "rating_sum",
|
| 506 |
-
"task_type": "regression",
|
| 507 |
-
"time_col": "timestamp"
|
| 508 |
-
},
|
| 509 |
-
{
|
| 510 |
-
"entity_table": "reviewers",
|
| 511 |
-
"kind": "forecast",
|
| 512 |
-
"name": "reviewer-return",
|
| 513 |
-
"splits": [
|
| 514 |
-
"train"
|
| 515 |
-
],
|
| 516 |
-
"target_col": "reviewer_returns",
|
| 517 |
-
"task_type": "binary_classification",
|
| 518 |
-
"time_col": "timestamp"
|
| 519 |
-
},
|
| 520 |
-
{
|
| 521 |
-
"entity_table": "reviewers",
|
| 522 |
-
"kind": "forecast",
|
| 523 |
-
"name": "reviewer-return-4x",
|
| 524 |
-
"splits": [
|
| 525 |
-
"train"
|
| 526 |
-
],
|
| 527 |
-
"target_col": "reviewer_returns_4x",
|
| 528 |
-
"task_type": "binary_classification",
|
| 529 |
-
"time_col": "timestamp"
|
| 530 |
-
},
|
| 531 |
-
{
|
| 532 |
-
"entity_table": "reviewers",
|
| 533 |
-
"kind": "forecast",
|
| 534 |
-
"name": "reviewer-return-5x",
|
| 535 |
-
"splits": [
|
| 536 |
-
"train"
|
| 537 |
-
],
|
| 538 |
-
"target_col": "reviewer_returns_5x",
|
| 539 |
-
"task_type": "binary_classification",
|
| 540 |
-
"time_col": "timestamp"
|
| 541 |
-
},
|
| 542 |
-
{
|
| 543 |
-
"entity_table": "reviewers",
|
| 544 |
-
"kind": "forecast",
|
| 545 |
-
"name": "reviewer-return-6x",
|
| 546 |
-
"splits": [
|
| 547 |
-
"train"
|
| 548 |
-
],
|
| 549 |
-
"target_col": "reviewer_returns_6x",
|
| 550 |
-
"task_type": "binary_classification",
|
| 551 |
-
"time_col": "timestamp"
|
| 552 |
-
},
|
| 553 |
-
{
|
| 554 |
-
"entity_table": "reviewers",
|
| 555 |
-
"kind": "forecast",
|
| 556 |
-
"name": "reviewer-return-7x",
|
| 557 |
-
"splits": [
|
| 558 |
-
"train"
|
| 559 |
-
],
|
| 560 |
-
"target_col": "reviewer_returns_7x",
|
| 561 |
-
"task_type": "binary_classification",
|
| 562 |
-
"time_col": "timestamp"
|
| 563 |
-
},
|
| 564 |
-
{
|
| 565 |
-
"entity_table": "reviewers",
|
| 566 |
-
"kind": "forecast",
|
| 567 |
-
"name": "reviewer-return-8x",
|
| 568 |
-
"splits": [
|
| 569 |
-
"train"
|
| 570 |
-
],
|
| 571 |
-
"target_col": "reviewer_returns_8x",
|
| 572 |
-
"task_type": "binary_classification",
|
| 573 |
-
"time_col": "timestamp"
|
| 574 |
-
},
|
| 575 |
-
{
|
| 576 |
-
"entity_table": "reviewers",
|
| 577 |
-
"kind": "forecast",
|
| 578 |
-
"name": "reviewer-review-3w",
|
| 579 |
-
"splits": [
|
| 580 |
-
"train"
|
| 581 |
-
],
|
| 582 |
-
"target_col": "reviewer_3w",
|
| 583 |
-
"task_type": "regression",
|
| 584 |
-
"time_col": "timestamp"
|
| 585 |
-
},
|
| 586 |
-
{
|
| 587 |
-
"entity_table": "reviewers",
|
| 588 |
-
"kind": "forecast",
|
| 589 |
-
"name": "reviewer-review-count",
|
| 590 |
-
"splits": [
|
| 591 |
-
"train"
|
| 592 |
-
],
|
| 593 |
-
"target_col": "predict_reviewer_review_count",
|
| 594 |
-
"task_type": "regression",
|
| 595 |
-
"time_col": "timestamp"
|
| 596 |
-
},
|
| 597 |
-
{
|
| 598 |
-
"entity_table": "reviewers",
|
| 599 |
-
"kind": "forecast",
|
| 600 |
-
"name": "reviewer-time-until-next-4x",
|
| 601 |
-
"splits": [
|
| 602 |
-
"train"
|
| 603 |
-
],
|
| 604 |
-
"target_col": "days_until_next_review_4x",
|
| 605 |
-
"task_type": "regression",
|
| 606 |
-
"time_col": "timestamp"
|
| 607 |
-
},
|
| 608 |
-
{
|
| 609 |
-
"entity_table": "reviewers",
|
| 610 |
-
"kind": "forecast",
|
| 611 |
-
"name": "reviewer-time-until-next-5x",
|
| 612 |
-
"splits": [
|
| 613 |
-
"train"
|
| 614 |
-
],
|
| 615 |
-
"target_col": "days_until_next_review_5x",
|
| 616 |
-
"task_type": "regression",
|
| 617 |
-
"time_col": "timestamp"
|
| 618 |
-
},
|
| 619 |
-
{
|
| 620 |
-
"entity_table": "reviewers",
|
| 621 |
-
"kind": "forecast",
|
| 622 |
-
"name": "reviewer-time-until-next-6x",
|
| 623 |
-
"splits": [
|
| 624 |
-
"train"
|
| 625 |
-
],
|
| 626 |
-
"target_col": "days_until_next_review_6x",
|
| 627 |
-
"task_type": "regression",
|
| 628 |
-
"time_col": "timestamp"
|
| 629 |
-
},
|
| 630 |
-
{
|
| 631 |
-
"entity_table": "reviewers",
|
| 632 |
-
"kind": "forecast",
|
| 633 |
-
"name": "reviewer-time-until-next-8x",
|
| 634 |
-
"splits": [
|
| 635 |
-
"train"
|
| 636 |
-
],
|
| 637 |
-
"target_col": "days_until_next_review_8x",
|
| 638 |
-
"task_type": "regression",
|
| 639 |
-
"time_col": "timestamp"
|
| 640 |
-
},
|
| 641 |
-
{
|
| 642 |
-
"entity_table": "reviewers",
|
| 643 |
-
"kind": "forecast",
|
| 644 |
-
"name": "reviewer-top-activity",
|
| 645 |
-
"splits": [
|
| 646 |
-
"train"
|
| 647 |
-
],
|
| 648 |
-
"target_col": "top_activity",
|
| 649 |
-
"task_type": "binary_classification",
|
| 650 |
-
"time_col": "timestamp"
|
| 651 |
-
},
|
| 652 |
-
{
|
| 653 |
-
"entity_table": "reviewers",
|
| 654 |
-
"kind": "forecast",
|
| 655 |
-
"name": "reviewer-verified-only",
|
| 656 |
-
"splits": [
|
| 657 |
-
"train"
|
| 658 |
-
],
|
| 659 |
-
"target_col": "all_verified_reviewer",
|
| 660 |
-
"task_type": "binary_classification",
|
| 661 |
-
"time_col": "timestamp"
|
| 662 |
-
},
|
| 663 |
-
{
|
| 664 |
-
"entity_table": "reviewers",
|
| 665 |
-
"kind": "forecast",
|
| 666 |
-
"name": "reviewer-verified-ratio",
|
| 667 |
-
"splits": [
|
| 668 |
-
"train"
|
| 669 |
-
],
|
| 670 |
-
"target_col": "pred_verified",
|
| 671 |
-
"task_type": "binary_classification",
|
| 672 |
-
"time_col": "timestamp"
|
| 673 |
-
},
|
| 674 |
-
{
|
| 675 |
-
"entity_table": "reviewers",
|
| 676 |
-
"kind": "forecast",
|
| 677 |
-
"name": "reviewer-will-review-fashion",
|
| 678 |
-
"splits": [
|
| 679 |
-
"train"
|
| 680 |
-
],
|
| 681 |
-
"target_col": "reviews_next",
|
| 682 |
-
"task_type": "binary_classification",
|
| 683 |
-
"time_col": "timestamp"
|
| 684 |
-
},
|
| 685 |
-
{
|
| 686 |
-
"entity_table": "reviews",
|
| 687 |
-
"kind": "autocomplete",
|
| 688 |
-
"name": "reviews-rating",
|
| 689 |
-
"splits": [],
|
| 690 |
-
"target_col": "rating",
|
| 691 |
-
"task_type": "regression",
|
| 692 |
-
"time_col": null
|
| 693 |
-
},
|
| 694 |
-
{
|
| 695 |
-
"entity_table": "reviews",
|
| 696 |
-
"kind": "autocomplete",
|
| 697 |
-
"name": "reviews-verified",
|
| 698 |
-
"splits": [],
|
| 699 |
-
"target_col": "verified",
|
| 700 |
-
"task_type": "binary_classification",
|
| 701 |
-
"time_col": null
|
| 702 |
-
}
|
| 703 |
-
],
|
| 704 |
-
"text_embeddings": {
|
| 705 |
-
"all-MiniLM-L12-v2": {
|
| 706 |
-
"file": "text_emb_all-MiniLM-L12-v2.bin",
|
| 707 |
-
"d_text": 384
|
| 708 |
-
}
|
| 709 |
-
}
|
| 710 |
-
}
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
join-amazon-fashion/nodes.rkyv
DELETED
|
@@ -1,3 +0,0 @@
|
|
| 1 |
-
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:e97586801ad6e9f683169125d18dcab340783864bc5a6893cf980ea4403c86fb
|
| 3 |
-
size 21526566688
|
|
|
|
|
|
|
|
|
|
|
|
join-amazon-fashion/offsets.rkyv
DELETED
|
@@ -1,3 +0,0 @@
|
|
| 1 |
-
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:a4f71fc16a4d1923f364fb9bf9f5b727d932b06aed49f4bc6d3a440e66ad958c
|
| 3 |
-
size 682802352
|
|
|
|
|
|
|
|
|
|
|
|
join-amazon-fashion/p2f_adj.rkyv
DELETED
|
@@ -1,3 +0,0 @@
|
|
| 1 |
-
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:8dce601b4eff624387568d89ab70b2a65796e6f43ad1cb1622021bb276db472e
|
| 3 |
-
size 3154117216
|
|
|
|
|
|
|
|
|
|
|
|
join-amazon-fashion/table_info.json
DELETED
|
@@ -1 +0,0 @@
|
|
| 1 |
-
{"reviewer-will-review-fashion:Train":{"node_idx_offset":81481827,"num_nodes":3868464},"product-unique-reviewers:Train":{"node_idx_offset":40601777,"num_nodes":1092139},"reviewers:Db":{"node_idx_offset":376858,"num_nodes":540375},"reviewer-distinct-products:Train":{"node_idx_offset":58601413,"num_nodes":661451},"reviewer-min-rating:Train":{"node_idx_offset":61908668,"num_nodes":661451},"product-verified-count:Train":{"node_idx_offset":41693916,"num_nodes":1092139},"product-churn-6x:Train":{"node_idx_offset":15081979,"num_nodes":1107514},"reviewer-time-until-next-6x:Train":{"node_idx_offset":77910001,"num_nodes":791825},"product-time-until-next-6x:Train":{"node_idx_offset":37834828,"num_nodes":582684},"product-top-review-volume:Train":{"node_idx_offset":38417512,"num_nodes":1092126},"product-churn-8x:Train":{"node_idx_offset":16189493,"num_nodes":999919},"product-review-count-3w:Train":{"node_idx_offset":33507369,"num_nodes":2377721},"reviewer-mean-rating:Train":{"node_idx_offset":61247217,"num_nodes":661451},"product-review-count:Train":{"node_idx_offset":30382258,"num_nodes":3125111},"product-rating-trend:Train":{"node_idx_offset":25585656,"num_nodes":751271},"reviewer-top-activity:Train":{"node_idx_offset":79497484,"num_nodes":661441},"products:Db":{"node_idx_offset":0,"num_nodes":376858},"product-rating-change:Train":{"node_idx_offset":24834385,"num_nodes":751271},"product-churn:Train":{"node_idx_offset":10127208,"num_nodes":3125111},"reviewer-verified-ratio:Train":{"node_idx_offset":80820376,"num_nodes":661451},"reviewer-return-7x:Train":{"node_idx_offset":67906547,"num_nodes":465736},"reviewer-max-rating:Train":{"node_idx_offset":60585766,"num_nodes":661451},"reviewer-return-8x:Train":{"node_idx_offset":68372283,"num_nodes":399180},"product-any-new-review:Train":{"node_idx_offset":7001941,"num_nodes":3125267},"product-max-rating:Train":{"node_idx_offset":19373690,"num_nodes":1092139},"product-churn-4x:Train":{"node_idx_offset":13252319,"num_nodes":1829660},"reviewer-review-3w:Train":{"node_idx_offset":68771463,"num_nodes":3460259},"reviewer-time-until-next-5x:Train":{"node_idx_offset":77130172,"num_nodes":779829},"reviewer-churn-5x:Train":{"node_idx_offset":53627695,"num_nodes":1802219},"reviewer-time-until-next-8x:Train":{"node_idx_offset":78701826,"num_nodes":795658},"product-mean-reviewer-id:Train":{"node_idx_offset":21557968,"num_nodes":1092139},"reviewer-return-6x:Train":{"node_idx_offset":67355305,"num_nodes":551242},"reviewer-return-5x:Train":{"node_idx_offset":66690672,"num_nodes":664633},"reviewer-rating-sum:Train":{"node_idx_offset":62570119,"num_nodes":661451},"product-min-rating:Train":{"node_idx_offset":22650107,"num_nodes":1092139},"product-verified-share:Train":{"node_idx_offset":42786055,"num_nodes":1092139},"reviews:Db":{"node_idx_offset":917233,"num_nodes":4992569},"product-reviewer-min-id:Train":{"node_idx_offset":35885090,"num_nodes":1092139},"reviewer-return:Train":{"node_idx_offset":63231570,"num_nodes":2244016},"product-mean-rating:Train":{"node_idx_offset":20465829,"num_nodes":1092139},"reviewer-harsh-critic:Train":{"node_idx_offset":59924315,"num_nodes":661451},"product-total-rating-sum:Train":{"node_idx_offset":39509638,"num_nodes":1092139},"product-return-6x:Train":{"node_idx_offset":28981774,"num_nodes":308345},"product-rating-volatility:Train":{"node_idx_offset":26336927,"num_nodes":495864},"reviewer-churn-6x:Train":{"node_idx_offset":55429914,"num_nodes":1670646},"reviewer-time-until-next-4x:Train":{"node_idx_offset":76100002,"num_nodes":1030170},"product-low-rating:Train":{"node_idx_offset":17189412,"num_nodes":1092139},"product-will-be-reviewed:Train":{"node_idx_offset":43878194,"num_nodes":3125267},"reviewer-generous:Train":{"node_idx_offset":59262864,"num_nodes":661451},"reviewer-return-4x:Train":{"node_idx_offset":65475586,"num_nodes":1215086},"reviewer-churn-8x:Train":{"node_idx_offset":57100560,"num_nodes":1500853},"product-popular-next-window:Train":{"node_idx_offset":23742246,"num_nodes":1092139},"product-return:Train":{"node_idx_offset":26832791,"num_nodes":1478714},"reviewer-verified-only:Train":{"node_idx_offset":80158925,"num_nodes":661451},"product-low-rating-event:Train":{"node_idx_offset":18281551,"num_nodes":1092139},"reviewer-churn:Train":{"node_idx_offset":47003461,"num_nodes":3868280},"reviewer-review-count:Train":{"node_idx_offset":72231722,"num_nodes":3868280},"product-return-4x:Train":{"node_idx_offset":28311505,"num_nodes":670269},"reviewer-churn-4x:Train":{"node_idx_offset":50871741,"num_nodes":2755954},"product-review-concentration:Train":{"node_idx_offset":29290119,"num_nodes":1092139},"product-all-verified:Train":{"node_idx_offset":5909802,"num_nodes":1092139},"product-time-until-next-4x:Train":{"node_idx_offset":36977229,"num_nodes":857599}}
|
|
|
|
|
|
join-amazon-fashion/text.json
DELETED
|
@@ -1,3 +0,0 @@
|
|
| 1 |
-
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:6ddaf4d02b5dfafc2b3059ab04c12586929bfc4343f11e75d26aebf0857cef77
|
| 3 |
-
size 240983425
|
|
|
|
|
|
|
|
|
|
|
|
join-amazon-fashion/text_emb_all-MiniLM-L12-v2.bin
DELETED
|
@@ -1,3 +0,0 @@
|
|
| 1 |
-
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:a1a14147c343370f98b8114b5ce2a610520d0588732f75e6fc8c586d1d2fbe97
|
| 3 |
-
size 572691456
|
|
|
|
|
|
|
|
|
|
|
|
join-amazon-movies/column_index.json
DELETED
|
@@ -1 +0,0 @@
|
|
| 1 |
-
{"long_review of movie-long-review":311736,"churned_6x of movie-churn-6x":13,"churned_8x of movie-churn-8x":311801,"movie_id of movie-rating-trend":311803,"rating of reviews":311080,"movie_id of movie-popular-next-window":311707,"reviewer_id of reviewer-return-8x":311723,"timestamp of reviewer-review-count":311761,"movie_id of movie-time-until-next-6x":231457,"top_activity of reviewer-top-activity":7,"timestamp of reviewer-return-6x":231486,"reviewer_id of reviewer-churn-8x":311062,"timestamp of movie-return-8x":311716,"reviews_next of reviewer-will-review-movie":311076,"returned_8x of reviewer-return-8x":311725,"movie_returns of movie-return":311777,"reviewer_id of reviewer-churn-5x":311719,"popular of movie-popular-next-window":311708,"movie_id of movie-min-rating":311747,"timestamp of movie-all-verified":311817,"timestamp of movie-churn-4x":311788,"timestamp of reviewer-time-until-next-8x":311741,"reviewer_id of reviewer-verified-ratio":311743,"book_has_review of movie-any-new-review":21,"reviewer_id of reviewer-long-writer":39,"movie_id of movie-low-rating":311807,"timestamp of reviewer-verified-only":231479,"movie_id of movie-return":311775,"timestamp of movie-mean-rating":231451,"price of movies":311056,"reviewer_range of movie-unique-reviewers":311752,"churned_4x of movie-churn-4x":311789,"reviewer_id of reviewer-review-count":311759,"movie_id of movie-verified-count":231441,"returned_5x of reviewer-return-5x":311757,"movie_id of reviews":311079,"timestamp of movie-low-rating":311809,"reviewer_id of reviewer-long-review-writer":311763,"returned_4x of reviewer-return-4x":231455,"reviewer_id of reviewer-return-6x":231485,"timestamp of reviewer-top-activity":8,"reviewer_id of reviewer-min-rating":231473,"timestamp of reviews":311081,"movie_id of movie-long-review":311735,"predict_movie_review_count of movie-review-count":311772,"movie_id of movies":231488,"returned_6x of movie-return-6x":311793,"movie_id of movie-all-verified":311815,"timestamp of movie-min-rating":311749,"verified of reviews":311082,"movie_id of movie-total-rating-sum":311767,"timestamp of reviewer-long-writer":41,"days_until_next of reviewer-time-until-next-5x":16,"timestamp of reviewer-will-review-movie":311075,"movie_id of movie-return-4x":35,"movie_id of movie-will-be-reviewed":231445,"title of movies":231489,"predict_reviewer_review_count of reviewer-review-count":311760,"all_verified_reviewer of reviewer-verified-only":231478,"timestamp of movie-return":311776,"timestamp of movie-churn-8x":311800,"rating_volatility of movie-rating-volatility":311812,"n_reviews of movies":311060,"days_until_next of reviewer-time-until-next-8x":311740,"timestamp of reviewer-max-rating":311068,"category of movies":311057,"timestamp of movie-total-rating-sum":311769,"long_writer of reviewer-long-writer":40,"rating_sum of reviewer-rating-sum":311712,"reviewer_id of reviewer-top-activity":6,"reviewer_min_rating of reviewer-min-rating":231474,"timestamp of reviewer-time-until-next-6x":311729,"harsh_critic of reviewer-harsh-critic":231470,"timestamp of reviewer-return":311796,"reviewer_id of reviewer-churn":231481,"days_until_next of movie-time-until-next-4x":24,"pred_rating of reviewer-mean-rating":311071,"reviewer_id of reviewer-verified-only":231477,"reviewer_id of reviewer-rating-sum":311711,"timestamp of reviewer-long-review-writer":311765,"low_rating of movie-low-rating":311808,"timestamp of movie-rating-volatility":311813,"timestamp of reviewer-distinct-movies":231467,"reviewer_max_rating of reviewer-max-rating":311067,"movie_id of movie-unique-reviewers":311751,"reviewer_id of reviewers":42,"reviewer_id of reviewer-return-5x":311755,"timestamp of movie-any-new-review":20,"reviewer_id of reviewer-time-until-next-5x":15,"reviewer_id of reviewer-churn-4x":27,"reviewer_id of reviewer-distinct-movies":231465,"movie_id of movie-low-rating-event":231461,"reviewer_id of reviewer-max-rating":311066,"reviewer_id of reviewer-time-until-next-8x":311739,"review_length_change of movie-review-length-change":311784,"timestamp of reviewer-time-until-next-5x":17,"timestamp of movie-top-review-volume":311781,"rating_trend of movie-rating-trend":311804,"churned_6x of reviewer-churn-6x":4,"timestamp of reviewer-churn-8x":311063,"review_len of reviews":311705,"reviewer_id of reviewer-time-until-next-6x":311727,"timestamp of movie-review-length-change":311785,"reviewer_id of reviewer-churn-6x":1,"movie_id of movie-return-6x":311791,"reviewer_returns of reviewer-return":311797,"days_until_next of reviewer-time-until-next-4x":32,"returned_4x of movie-return-4x":37,"low_rating_event of movie-low-rating-event":231462,"timestamp of movie-return-6x":311792,"timestamp of movie-churn":311732,"movie_id of movie-rating-volatility":311811,"timestamp of movie-popular-next-window":311709,"timestamp of movie-rating-trend":311805,"min_rating of movie-min-rating":311748,"rating_sum of movie-total-rating-sum":311768,"all_verified of movie-all-verified":311816,"timestamp of reviewer-return-4x":231454,"movie_id of movie-mean-rating":231449,"movie_id of movie-time-until-next-4x":23,"reviewer_id of reviewer-time-until-next-4x":31,"reviewer_id of reviewer-will-review-movie":311074,"timestamp of movie-time-until-next-4x":25,"reviewer_id of reviewer-mean-rating":311070,"movie_id of movie-churn":311731,"timestamp of reviewer-rating-sum":311713,"movie_id of movie-churn-6x":10,"timestamp of movie-will-be-reviewed":231446,"pred_rating of movie-mean-rating":231450,"movie_id of movie-any-new-review":19,"reviewer_id of reviewer-return-4x":231453,"timestamp of reviewer-min-rating":231475,"timestamp of movie-review-count":311773,"timestamp of movie-long-review":311737,"reviewer_id of reviews":311078,"churned_8x of reviewer-churn-8x":311064,"movie_id of movie-top-review-volume":311779,"movie_id of movie-return-8x":311715,"predict_reviewer_churn of reviewer-churn":231483,"movie_id of movie-churn-4x":311787,"churned_4x of reviewer-churn-4x":29,"reviewer_id of reviewer-harsh-critic":231469,"reviewer_name of reviewers":43,"timestamp of movie-time-until-next-6x":231459,"timestamp of reviewer-mean-rating":311072,"churned_5x of reviewer-churn-5x":311721,"predict_movie_churn of movie-churn":311733,"returned_8x of movie-return-8x":311717,"timestamp of reviewer-verified-ratio":311745,"distinct_movies of reviewer-distinct-movies":231466,"timestamp of reviewer-return-5x":311756,"brand of movies":289475,"timestamp of movie-churn-6x":12,"timestamp of movie-return-4x":36,"timestamp of reviewer-churn":231482,"vote of reviews":311083,"movie_id of movie-review-count":311771,"pred_verified of reviewer-verified-ratio":311744,"days_until_next of movie-time-until-next-6x":231458,"timestamp of movie-low-rating-event":231463,"timestamp of reviewer-churn-4x":28,"reviewed_next of movie-will-be-reviewed":231447,"timestamp of reviewer-churn-5x":311720,"avg_rating of movies":311059,"verified_count of movie-verified-count":231442,"verbose_reviewer of reviewer-long-review-writer":311764,"timestamp of reviewer-return-8x":311724,"timestamp of reviewer-time-until-next-4x":33,"top_review_volume of movie-top-review-volume":311780,"movie_id of movie-review-length-change":311783,"reviewer_id of reviewer-return":311795,"days_until_next of reviewer-time-until-next-6x":311728,"timestamp of reviewer-churn-6x":3,"timestamp of reviewer-harsh-critic":231471,"timestamp of movie-unique-reviewers":311753,"movie_id of movie-churn-8x":311799,"timestamp of movie-verified-count":231443,"returned_6x of reviewer-return-6x":231487}
|
|
|
|
|
|
join-amazon-movies/meta.json
DELETED
|
@@ -1,664 +0,0 @@
|
|
| 1 |
-
{
|
| 2 |
-
"files": {
|
| 3 |
-
"column_index": "column_index.json",
|
| 4 |
-
"nodes": "nodes.rkyv",
|
| 5 |
-
"offsets": "offsets.rkyv",
|
| 6 |
-
"p2f_adj": "p2f_adj.rkyv",
|
| 7 |
-
"table_info": "table_info.json",
|
| 8 |
-
"text": "text.json"
|
| 9 |
-
},
|
| 10 |
-
"format_version": 1,
|
| 11 |
-
"name": "join-amazon-movies",
|
| 12 |
-
"num_db_tables": 3,
|
| 13 |
-
"num_nodes": 38682006,
|
| 14 |
-
"num_task_tables": 54,
|
| 15 |
-
"num_text_strings": 311818,
|
| 16 |
-
"source": "stanford-star/the-join/join-amazon-movies",
|
| 17 |
-
"tasks": [
|
| 18 |
-
{
|
| 19 |
-
"entity_table": "movies",
|
| 20 |
-
"kind": "forecast",
|
| 21 |
-
"name": "movie-all-verified",
|
| 22 |
-
"splits": [
|
| 23 |
-
"train"
|
| 24 |
-
],
|
| 25 |
-
"target_col": "all_verified",
|
| 26 |
-
"task_type": "binary_classification",
|
| 27 |
-
"time_col": "timestamp"
|
| 28 |
-
},
|
| 29 |
-
{
|
| 30 |
-
"entity_table": "movies",
|
| 31 |
-
"kind": "forecast",
|
| 32 |
-
"name": "movie-any-new-review",
|
| 33 |
-
"splits": [
|
| 34 |
-
"train"
|
| 35 |
-
],
|
| 36 |
-
"target_col": "book_has_review",
|
| 37 |
-
"task_type": "binary_classification",
|
| 38 |
-
"time_col": "timestamp"
|
| 39 |
-
},
|
| 40 |
-
{
|
| 41 |
-
"entity_table": "movies",
|
| 42 |
-
"kind": "forecast",
|
| 43 |
-
"name": "movie-churn",
|
| 44 |
-
"splits": [
|
| 45 |
-
"train"
|
| 46 |
-
],
|
| 47 |
-
"target_col": "predict_movie_churn",
|
| 48 |
-
"task_type": "binary_classification",
|
| 49 |
-
"time_col": "timestamp"
|
| 50 |
-
},
|
| 51 |
-
{
|
| 52 |
-
"entity_table": "movies",
|
| 53 |
-
"kind": "forecast",
|
| 54 |
-
"name": "movie-churn-4x",
|
| 55 |
-
"splits": [
|
| 56 |
-
"train"
|
| 57 |
-
],
|
| 58 |
-
"target_col": "churned_4x",
|
| 59 |
-
"task_type": "binary_classification",
|
| 60 |
-
"time_col": "timestamp"
|
| 61 |
-
},
|
| 62 |
-
{
|
| 63 |
-
"entity_table": "movies",
|
| 64 |
-
"kind": "forecast",
|
| 65 |
-
"name": "movie-churn-6x",
|
| 66 |
-
"splits": [
|
| 67 |
-
"train"
|
| 68 |
-
],
|
| 69 |
-
"target_col": "churned_6x",
|
| 70 |
-
"task_type": "binary_classification",
|
| 71 |
-
"time_col": "timestamp"
|
| 72 |
-
},
|
| 73 |
-
{
|
| 74 |
-
"entity_table": "movies",
|
| 75 |
-
"kind": "forecast",
|
| 76 |
-
"name": "movie-churn-8x",
|
| 77 |
-
"splits": [
|
| 78 |
-
"train"
|
| 79 |
-
],
|
| 80 |
-
"target_col": "churned_8x",
|
| 81 |
-
"task_type": "binary_classification",
|
| 82 |
-
"time_col": "timestamp"
|
| 83 |
-
},
|
| 84 |
-
{
|
| 85 |
-
"entity_table": "movies",
|
| 86 |
-
"kind": "forecast",
|
| 87 |
-
"name": "movie-long-review",
|
| 88 |
-
"splits": [
|
| 89 |
-
"train"
|
| 90 |
-
],
|
| 91 |
-
"target_col": "long_review",
|
| 92 |
-
"task_type": "binary_classification",
|
| 93 |
-
"time_col": "timestamp"
|
| 94 |
-
},
|
| 95 |
-
{
|
| 96 |
-
"entity_table": "movies",
|
| 97 |
-
"kind": "forecast",
|
| 98 |
-
"name": "movie-low-rating",
|
| 99 |
-
"splits": [
|
| 100 |
-
"train"
|
| 101 |
-
],
|
| 102 |
-
"target_col": "low_rating",
|
| 103 |
-
"task_type": "binary_classification",
|
| 104 |
-
"time_col": "timestamp"
|
| 105 |
-
},
|
| 106 |
-
{
|
| 107 |
-
"entity_table": "movies",
|
| 108 |
-
"kind": "forecast",
|
| 109 |
-
"name": "movie-low-rating-event",
|
| 110 |
-
"splits": [
|
| 111 |
-
"train"
|
| 112 |
-
],
|
| 113 |
-
"target_col": "low_rating_event",
|
| 114 |
-
"task_type": "binary_classification",
|
| 115 |
-
"time_col": "timestamp"
|
| 116 |
-
},
|
| 117 |
-
{
|
| 118 |
-
"entity_table": "movies",
|
| 119 |
-
"kind": "forecast",
|
| 120 |
-
"name": "movie-mean-rating",
|
| 121 |
-
"splits": [
|
| 122 |
-
"train"
|
| 123 |
-
],
|
| 124 |
-
"target_col": "pred_rating",
|
| 125 |
-
"task_type": "regression",
|
| 126 |
-
"time_col": "timestamp"
|
| 127 |
-
},
|
| 128 |
-
{
|
| 129 |
-
"entity_table": "movies",
|
| 130 |
-
"kind": "forecast",
|
| 131 |
-
"name": "movie-min-rating",
|
| 132 |
-
"splits": [
|
| 133 |
-
"train"
|
| 134 |
-
],
|
| 135 |
-
"target_col": "min_rating",
|
| 136 |
-
"task_type": "regression",
|
| 137 |
-
"time_col": "timestamp"
|
| 138 |
-
},
|
| 139 |
-
{
|
| 140 |
-
"entity_table": "movies",
|
| 141 |
-
"kind": "forecast",
|
| 142 |
-
"name": "movie-popular-next-window",
|
| 143 |
-
"splits": [
|
| 144 |
-
"train"
|
| 145 |
-
],
|
| 146 |
-
"target_col": "popular",
|
| 147 |
-
"task_type": "binary_classification",
|
| 148 |
-
"time_col": "timestamp"
|
| 149 |
-
},
|
| 150 |
-
{
|
| 151 |
-
"entity_table": "movies",
|
| 152 |
-
"kind": "forecast",
|
| 153 |
-
"name": "movie-rating-trend",
|
| 154 |
-
"splits": [
|
| 155 |
-
"train"
|
| 156 |
-
],
|
| 157 |
-
"target_col": "rating_trend",
|
| 158 |
-
"task_type": "binary_classification",
|
| 159 |
-
"time_col": "timestamp"
|
| 160 |
-
},
|
| 161 |
-
{
|
| 162 |
-
"entity_table": "movies",
|
| 163 |
-
"kind": "forecast",
|
| 164 |
-
"name": "movie-rating-volatility",
|
| 165 |
-
"splits": [
|
| 166 |
-
"train"
|
| 167 |
-
],
|
| 168 |
-
"target_col": "rating_volatility",
|
| 169 |
-
"task_type": "regression",
|
| 170 |
-
"time_col": "timestamp"
|
| 171 |
-
},
|
| 172 |
-
{
|
| 173 |
-
"entity_table": "movies",
|
| 174 |
-
"kind": "forecast",
|
| 175 |
-
"name": "movie-return",
|
| 176 |
-
"splits": [
|
| 177 |
-
"train"
|
| 178 |
-
],
|
| 179 |
-
"target_col": "movie_returns",
|
| 180 |
-
"task_type": "binary_classification",
|
| 181 |
-
"time_col": "timestamp"
|
| 182 |
-
},
|
| 183 |
-
{
|
| 184 |
-
"entity_table": "movies",
|
| 185 |
-
"kind": "forecast",
|
| 186 |
-
"name": "movie-return-4x",
|
| 187 |
-
"splits": [
|
| 188 |
-
"train"
|
| 189 |
-
],
|
| 190 |
-
"target_col": "returned_4x",
|
| 191 |
-
"task_type": "binary_classification",
|
| 192 |
-
"time_col": "timestamp"
|
| 193 |
-
},
|
| 194 |
-
{
|
| 195 |
-
"entity_table": "movies",
|
| 196 |
-
"kind": "forecast",
|
| 197 |
-
"name": "movie-return-6x",
|
| 198 |
-
"splits": [
|
| 199 |
-
"train"
|
| 200 |
-
],
|
| 201 |
-
"target_col": "returned_6x",
|
| 202 |
-
"task_type": "binary_classification",
|
| 203 |
-
"time_col": "timestamp"
|
| 204 |
-
},
|
| 205 |
-
{
|
| 206 |
-
"entity_table": "movies",
|
| 207 |
-
"kind": "forecast",
|
| 208 |
-
"name": "movie-return-8x",
|
| 209 |
-
"splits": [
|
| 210 |
-
"train"
|
| 211 |
-
],
|
| 212 |
-
"target_col": "returned_8x",
|
| 213 |
-
"task_type": "binary_classification",
|
| 214 |
-
"time_col": "timestamp"
|
| 215 |
-
},
|
| 216 |
-
{
|
| 217 |
-
"entity_table": "movies",
|
| 218 |
-
"kind": "forecast",
|
| 219 |
-
"name": "movie-review-count",
|
| 220 |
-
"splits": [
|
| 221 |
-
"train"
|
| 222 |
-
],
|
| 223 |
-
"target_col": "predict_movie_review_count",
|
| 224 |
-
"task_type": "regression",
|
| 225 |
-
"time_col": "timestamp"
|
| 226 |
-
},
|
| 227 |
-
{
|
| 228 |
-
"entity_table": "movies",
|
| 229 |
-
"kind": "forecast",
|
| 230 |
-
"name": "movie-review-length-change",
|
| 231 |
-
"splits": [
|
| 232 |
-
"train"
|
| 233 |
-
],
|
| 234 |
-
"target_col": "review_length_change",
|
| 235 |
-
"task_type": "regression",
|
| 236 |
-
"time_col": "timestamp"
|
| 237 |
-
},
|
| 238 |
-
{
|
| 239 |
-
"entity_table": "movies",
|
| 240 |
-
"kind": "forecast",
|
| 241 |
-
"name": "movie-time-until-next-4x",
|
| 242 |
-
"splits": [
|
| 243 |
-
"train"
|
| 244 |
-
],
|
| 245 |
-
"target_col": "days_until_next",
|
| 246 |
-
"task_type": "regression",
|
| 247 |
-
"time_col": "timestamp"
|
| 248 |
-
},
|
| 249 |
-
{
|
| 250 |
-
"entity_table": "movies",
|
| 251 |
-
"kind": "forecast",
|
| 252 |
-
"name": "movie-time-until-next-6x",
|
| 253 |
-
"splits": [
|
| 254 |
-
"train"
|
| 255 |
-
],
|
| 256 |
-
"target_col": "days_until_next",
|
| 257 |
-
"task_type": "regression",
|
| 258 |
-
"time_col": "timestamp"
|
| 259 |
-
},
|
| 260 |
-
{
|
| 261 |
-
"entity_table": "movies",
|
| 262 |
-
"kind": "forecast",
|
| 263 |
-
"name": "movie-top-review-volume",
|
| 264 |
-
"splits": [
|
| 265 |
-
"train"
|
| 266 |
-
],
|
| 267 |
-
"target_col": "top_review_volume",
|
| 268 |
-
"task_type": "binary_classification",
|
| 269 |
-
"time_col": "timestamp"
|
| 270 |
-
},
|
| 271 |
-
{
|
| 272 |
-
"entity_table": "movies",
|
| 273 |
-
"kind": "forecast",
|
| 274 |
-
"name": "movie-total-rating-sum",
|
| 275 |
-
"splits": [
|
| 276 |
-
"train"
|
| 277 |
-
],
|
| 278 |
-
"target_col": "rating_sum",
|
| 279 |
-
"task_type": "regression",
|
| 280 |
-
"time_col": "timestamp"
|
| 281 |
-
},
|
| 282 |
-
{
|
| 283 |
-
"entity_table": "movies",
|
| 284 |
-
"kind": "forecast",
|
| 285 |
-
"name": "movie-unique-reviewers",
|
| 286 |
-
"splits": [
|
| 287 |
-
"train"
|
| 288 |
-
],
|
| 289 |
-
"target_col": "reviewer_range",
|
| 290 |
-
"task_type": "regression",
|
| 291 |
-
"time_col": "timestamp"
|
| 292 |
-
},
|
| 293 |
-
{
|
| 294 |
-
"entity_table": "movies",
|
| 295 |
-
"kind": "forecast",
|
| 296 |
-
"name": "movie-verified-count",
|
| 297 |
-
"splits": [
|
| 298 |
-
"train"
|
| 299 |
-
],
|
| 300 |
-
"target_col": "verified_count",
|
| 301 |
-
"task_type": "regression",
|
| 302 |
-
"time_col": "timestamp"
|
| 303 |
-
},
|
| 304 |
-
{
|
| 305 |
-
"entity_table": "movies",
|
| 306 |
-
"kind": "forecast",
|
| 307 |
-
"name": "movie-will-be-reviewed",
|
| 308 |
-
"splits": [
|
| 309 |
-
"train"
|
| 310 |
-
],
|
| 311 |
-
"target_col": "reviewed_next",
|
| 312 |
-
"task_type": "binary_classification",
|
| 313 |
-
"time_col": "timestamp"
|
| 314 |
-
},
|
| 315 |
-
{
|
| 316 |
-
"entity_table": "movies",
|
| 317 |
-
"kind": "autocomplete",
|
| 318 |
-
"name": "movies-avg_rating",
|
| 319 |
-
"splits": [],
|
| 320 |
-
"target_col": "avg_rating",
|
| 321 |
-
"task_type": "regression",
|
| 322 |
-
"time_col": null
|
| 323 |
-
},
|
| 324 |
-
{
|
| 325 |
-
"entity_table": "movies",
|
| 326 |
-
"kind": "autocomplete",
|
| 327 |
-
"name": "movies-n_reviews",
|
| 328 |
-
"splits": [],
|
| 329 |
-
"target_col": "n_reviews",
|
| 330 |
-
"task_type": "regression",
|
| 331 |
-
"time_col": null
|
| 332 |
-
},
|
| 333 |
-
{
|
| 334 |
-
"entity_table": "reviewers",
|
| 335 |
-
"kind": "forecast",
|
| 336 |
-
"name": "reviewer-churn",
|
| 337 |
-
"splits": [
|
| 338 |
-
"train"
|
| 339 |
-
],
|
| 340 |
-
"target_col": "predict_reviewer_churn",
|
| 341 |
-
"task_type": "binary_classification",
|
| 342 |
-
"time_col": "timestamp"
|
| 343 |
-
},
|
| 344 |
-
{
|
| 345 |
-
"entity_table": "reviewers",
|
| 346 |
-
"kind": "forecast",
|
| 347 |
-
"name": "reviewer-churn-4x",
|
| 348 |
-
"splits": [
|
| 349 |
-
"train"
|
| 350 |
-
],
|
| 351 |
-
"target_col": "churned_4x",
|
| 352 |
-
"task_type": "binary_classification",
|
| 353 |
-
"time_col": "timestamp"
|
| 354 |
-
},
|
| 355 |
-
{
|
| 356 |
-
"entity_table": "reviewers",
|
| 357 |
-
"kind": "forecast",
|
| 358 |
-
"name": "reviewer-churn-5x",
|
| 359 |
-
"splits": [
|
| 360 |
-
"train"
|
| 361 |
-
],
|
| 362 |
-
"target_col": "churned_5x",
|
| 363 |
-
"task_type": "binary_classification",
|
| 364 |
-
"time_col": "timestamp"
|
| 365 |
-
},
|
| 366 |
-
{
|
| 367 |
-
"entity_table": "reviewers",
|
| 368 |
-
"kind": "forecast",
|
| 369 |
-
"name": "reviewer-churn-6x",
|
| 370 |
-
"splits": [
|
| 371 |
-
"train"
|
| 372 |
-
],
|
| 373 |
-
"target_col": "churned_6x",
|
| 374 |
-
"task_type": "binary_classification",
|
| 375 |
-
"time_col": "timestamp"
|
| 376 |
-
},
|
| 377 |
-
{
|
| 378 |
-
"entity_table": "reviewers",
|
| 379 |
-
"kind": "forecast",
|
| 380 |
-
"name": "reviewer-churn-8x",
|
| 381 |
-
"splits": [
|
| 382 |
-
"train"
|
| 383 |
-
],
|
| 384 |
-
"target_col": "churned_8x",
|
| 385 |
-
"task_type": "binary_classification",
|
| 386 |
-
"time_col": "timestamp"
|
| 387 |
-
},
|
| 388 |
-
{
|
| 389 |
-
"entity_table": "reviewers",
|
| 390 |
-
"kind": "forecast",
|
| 391 |
-
"name": "reviewer-distinct-movies",
|
| 392 |
-
"splits": [
|
| 393 |
-
"train"
|
| 394 |
-
],
|
| 395 |
-
"target_col": "distinct_movies",
|
| 396 |
-
"task_type": "regression",
|
| 397 |
-
"time_col": "timestamp"
|
| 398 |
-
},
|
| 399 |
-
{
|
| 400 |
-
"entity_table": "reviewers",
|
| 401 |
-
"kind": "forecast",
|
| 402 |
-
"name": "reviewer-harsh-critic",
|
| 403 |
-
"splits": [
|
| 404 |
-
"train"
|
| 405 |
-
],
|
| 406 |
-
"target_col": "harsh_critic",
|
| 407 |
-
"task_type": "binary_classification",
|
| 408 |
-
"time_col": "timestamp"
|
| 409 |
-
},
|
| 410 |
-
{
|
| 411 |
-
"entity_table": "reviewers",
|
| 412 |
-
"kind": "forecast",
|
| 413 |
-
"name": "reviewer-long-review-writer",
|
| 414 |
-
"splits": [
|
| 415 |
-
"train"
|
| 416 |
-
],
|
| 417 |
-
"target_col": "verbose_reviewer",
|
| 418 |
-
"task_type": "binary_classification",
|
| 419 |
-
"time_col": "timestamp"
|
| 420 |
-
},
|
| 421 |
-
{
|
| 422 |
-
"entity_table": "reviewers",
|
| 423 |
-
"kind": "forecast",
|
| 424 |
-
"name": "reviewer-long-writer",
|
| 425 |
-
"splits": [
|
| 426 |
-
"train"
|
| 427 |
-
],
|
| 428 |
-
"target_col": "long_writer",
|
| 429 |
-
"task_type": "binary_classification",
|
| 430 |
-
"time_col": "timestamp"
|
| 431 |
-
},
|
| 432 |
-
{
|
| 433 |
-
"entity_table": "reviewers",
|
| 434 |
-
"kind": "forecast",
|
| 435 |
-
"name": "reviewer-max-rating",
|
| 436 |
-
"splits": [
|
| 437 |
-
"train"
|
| 438 |
-
],
|
| 439 |
-
"target_col": "reviewer_max_rating",
|
| 440 |
-
"task_type": "regression",
|
| 441 |
-
"time_col": "timestamp"
|
| 442 |
-
},
|
| 443 |
-
{
|
| 444 |
-
"entity_table": "reviewers",
|
| 445 |
-
"kind": "forecast",
|
| 446 |
-
"name": "reviewer-mean-rating",
|
| 447 |
-
"splits": [
|
| 448 |
-
"train"
|
| 449 |
-
],
|
| 450 |
-
"target_col": "pred_rating",
|
| 451 |
-
"task_type": "regression",
|
| 452 |
-
"time_col": "timestamp"
|
| 453 |
-
},
|
| 454 |
-
{
|
| 455 |
-
"entity_table": "reviewers",
|
| 456 |
-
"kind": "forecast",
|
| 457 |
-
"name": "reviewer-min-rating",
|
| 458 |
-
"splits": [
|
| 459 |
-
"train"
|
| 460 |
-
],
|
| 461 |
-
"target_col": "reviewer_min_rating",
|
| 462 |
-
"task_type": "regression",
|
| 463 |
-
"time_col": "timestamp"
|
| 464 |
-
},
|
| 465 |
-
{
|
| 466 |
-
"entity_table": "reviewers",
|
| 467 |
-
"kind": "forecast",
|
| 468 |
-
"name": "reviewer-rating-sum",
|
| 469 |
-
"splits": [
|
| 470 |
-
"train"
|
| 471 |
-
],
|
| 472 |
-
"target_col": "rating_sum",
|
| 473 |
-
"task_type": "regression",
|
| 474 |
-
"time_col": "timestamp"
|
| 475 |
-
},
|
| 476 |
-
{
|
| 477 |
-
"entity_table": "reviewers",
|
| 478 |
-
"kind": "forecast",
|
| 479 |
-
"name": "reviewer-return",
|
| 480 |
-
"splits": [
|
| 481 |
-
"train"
|
| 482 |
-
],
|
| 483 |
-
"target_col": "reviewer_returns",
|
| 484 |
-
"task_type": "binary_classification",
|
| 485 |
-
"time_col": "timestamp"
|
| 486 |
-
},
|
| 487 |
-
{
|
| 488 |
-
"entity_table": "reviewers",
|
| 489 |
-
"kind": "forecast",
|
| 490 |
-
"name": "reviewer-return-4x",
|
| 491 |
-
"splits": [
|
| 492 |
-
"train"
|
| 493 |
-
],
|
| 494 |
-
"target_col": "returned_4x",
|
| 495 |
-
"task_type": "binary_classification",
|
| 496 |
-
"time_col": "timestamp"
|
| 497 |
-
},
|
| 498 |
-
{
|
| 499 |
-
"entity_table": "reviewers",
|
| 500 |
-
"kind": "forecast",
|
| 501 |
-
"name": "reviewer-return-5x",
|
| 502 |
-
"splits": [
|
| 503 |
-
"train"
|
| 504 |
-
],
|
| 505 |
-
"target_col": "returned_5x",
|
| 506 |
-
"task_type": "binary_classification",
|
| 507 |
-
"time_col": "timestamp"
|
| 508 |
-
},
|
| 509 |
-
{
|
| 510 |
-
"entity_table": "reviewers",
|
| 511 |
-
"kind": "forecast",
|
| 512 |
-
"name": "reviewer-return-6x",
|
| 513 |
-
"splits": [
|
| 514 |
-
"train"
|
| 515 |
-
],
|
| 516 |
-
"target_col": "returned_6x",
|
| 517 |
-
"task_type": "binary_classification",
|
| 518 |
-
"time_col": "timestamp"
|
| 519 |
-
},
|
| 520 |
-
{
|
| 521 |
-
"entity_table": "reviewers",
|
| 522 |
-
"kind": "forecast",
|
| 523 |
-
"name": "reviewer-return-8x",
|
| 524 |
-
"splits": [
|
| 525 |
-
"train"
|
| 526 |
-
],
|
| 527 |
-
"target_col": "returned_8x",
|
| 528 |
-
"task_type": "binary_classification",
|
| 529 |
-
"time_col": "timestamp"
|
| 530 |
-
},
|
| 531 |
-
{
|
| 532 |
-
"entity_table": "reviewers",
|
| 533 |
-
"kind": "forecast",
|
| 534 |
-
"name": "reviewer-review-count",
|
| 535 |
-
"splits": [
|
| 536 |
-
"train"
|
| 537 |
-
],
|
| 538 |
-
"target_col": "predict_reviewer_review_count",
|
| 539 |
-
"task_type": "regression",
|
| 540 |
-
"time_col": "timestamp"
|
| 541 |
-
},
|
| 542 |
-
{
|
| 543 |
-
"entity_table": "reviewers",
|
| 544 |
-
"kind": "forecast",
|
| 545 |
-
"name": "reviewer-time-until-next-4x",
|
| 546 |
-
"splits": [
|
| 547 |
-
"train"
|
| 548 |
-
],
|
| 549 |
-
"target_col": "days_until_next",
|
| 550 |
-
"task_type": "regression",
|
| 551 |
-
"time_col": "timestamp"
|
| 552 |
-
},
|
| 553 |
-
{
|
| 554 |
-
"entity_table": "reviewers",
|
| 555 |
-
"kind": "forecast",
|
| 556 |
-
"name": "reviewer-time-until-next-5x",
|
| 557 |
-
"splits": [
|
| 558 |
-
"train"
|
| 559 |
-
],
|
| 560 |
-
"target_col": "days_until_next",
|
| 561 |
-
"task_type": "regression",
|
| 562 |
-
"time_col": "timestamp"
|
| 563 |
-
},
|
| 564 |
-
{
|
| 565 |
-
"entity_table": "reviewers",
|
| 566 |
-
"kind": "forecast",
|
| 567 |
-
"name": "reviewer-time-until-next-6x",
|
| 568 |
-
"splits": [
|
| 569 |
-
"train"
|
| 570 |
-
],
|
| 571 |
-
"target_col": "days_until_next",
|
| 572 |
-
"task_type": "regression",
|
| 573 |
-
"time_col": "timestamp"
|
| 574 |
-
},
|
| 575 |
-
{
|
| 576 |
-
"entity_table": "reviewers",
|
| 577 |
-
"kind": "forecast",
|
| 578 |
-
"name": "reviewer-time-until-next-8x",
|
| 579 |
-
"splits": [
|
| 580 |
-
"train"
|
| 581 |
-
],
|
| 582 |
-
"target_col": "days_until_next",
|
| 583 |
-
"task_type": "regression",
|
| 584 |
-
"time_col": "timestamp"
|
| 585 |
-
},
|
| 586 |
-
{
|
| 587 |
-
"entity_table": "reviewers",
|
| 588 |
-
"kind": "forecast",
|
| 589 |
-
"name": "reviewer-top-activity",
|
| 590 |
-
"splits": [
|
| 591 |
-
"train"
|
| 592 |
-
],
|
| 593 |
-
"target_col": "top_activity",
|
| 594 |
-
"task_type": "binary_classification",
|
| 595 |
-
"time_col": "timestamp"
|
| 596 |
-
},
|
| 597 |
-
{
|
| 598 |
-
"entity_table": "reviewers",
|
| 599 |
-
"kind": "forecast",
|
| 600 |
-
"name": "reviewer-verified-only",
|
| 601 |
-
"splits": [
|
| 602 |
-
"train"
|
| 603 |
-
],
|
| 604 |
-
"target_col": "all_verified_reviewer",
|
| 605 |
-
"task_type": "binary_classification",
|
| 606 |
-
"time_col": "timestamp"
|
| 607 |
-
},
|
| 608 |
-
{
|
| 609 |
-
"entity_table": "reviewers",
|
| 610 |
-
"kind": "forecast",
|
| 611 |
-
"name": "reviewer-verified-ratio",
|
| 612 |
-
"splits": [
|
| 613 |
-
"train"
|
| 614 |
-
],
|
| 615 |
-
"target_col": "pred_verified",
|
| 616 |
-
"task_type": "binary_classification",
|
| 617 |
-
"time_col": "timestamp"
|
| 618 |
-
},
|
| 619 |
-
{
|
| 620 |
-
"entity_table": "reviewers",
|
| 621 |
-
"kind": "forecast",
|
| 622 |
-
"name": "reviewer-will-review-movie",
|
| 623 |
-
"splits": [
|
| 624 |
-
"train"
|
| 625 |
-
],
|
| 626 |
-
"target_col": "reviews_next",
|
| 627 |
-
"task_type": "binary_classification",
|
| 628 |
-
"time_col": "timestamp"
|
| 629 |
-
},
|
| 630 |
-
{
|
| 631 |
-
"entity_table": "reviews",
|
| 632 |
-
"kind": "autocomplete",
|
| 633 |
-
"name": "reviews-rating",
|
| 634 |
-
"splits": [],
|
| 635 |
-
"target_col": "rating",
|
| 636 |
-
"task_type": "regression",
|
| 637 |
-
"time_col": null
|
| 638 |
-
},
|
| 639 |
-
{
|
| 640 |
-
"entity_table": "reviews",
|
| 641 |
-
"kind": "autocomplete",
|
| 642 |
-
"name": "reviews-review_len",
|
| 643 |
-
"splits": [],
|
| 644 |
-
"target_col": "review_len",
|
| 645 |
-
"task_type": "regression",
|
| 646 |
-
"time_col": null
|
| 647 |
-
},
|
| 648 |
-
{
|
| 649 |
-
"entity_table": "reviews",
|
| 650 |
-
"kind": "autocomplete",
|
| 651 |
-
"name": "reviews-verified",
|
| 652 |
-
"splits": [],
|
| 653 |
-
"target_col": "verified",
|
| 654 |
-
"task_type": "binary_classification",
|
| 655 |
-
"time_col": null
|
| 656 |
-
}
|
| 657 |
-
],
|
| 658 |
-
"text_embeddings": {
|
| 659 |
-
"all-MiniLM-L12-v2": {
|
| 660 |
-
"file": "text_emb_all-MiniLM-L12-v2.bin",
|
| 661 |
-
"d_text": 384
|
| 662 |
-
}
|
| 663 |
-
}
|
| 664 |
-
}
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
join-amazon-movies/nodes.rkyv
DELETED
|
@@ -1,3 +0,0 @@
|
|
| 1 |
-
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:eb7a8b8f15f412f09716f9a20d976def1b62baede884608de2a8c74641b783fe
|
| 3 |
-
size 9843640704
|
|
|
|
|
|
|
|
|
|
|
|
join-amazon-movies/offsets.rkyv
DELETED
|
@@ -1,3 +0,0 @@
|
|
| 1 |
-
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:ccd305fbc901ec4c1c95151da54749d46cc36fe542d8ece59c122a507444b167
|
| 3 |
-
size 309456072
|
|
|
|
|
|
|
|
|
|
|
|
join-amazon-movies/p2f_adj.rkyv
DELETED
|
@@ -1,3 +0,0 @@
|
|
| 1 |
-
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:92fc68540a54ded79ddbd62e697740acd14ae6e7df3235f3c0b18ceb8fb84807
|
| 3 |
-
size 1453598536
|
|
|
|
|
|
|
|
|
|
|
|
join-amazon-movies/table_info.json
DELETED
|
@@ -1 +0,0 @@
|
|
| 1 |
-
{"reviewer-time-until-next-5x:Train":{"node_idx_offset":34017122,"num_nodes":508896},"reviewer-churn-4x:Train":{"node_idx_offset":20764286,"num_nodes":1357979},"movie-total-rating-sum:Train":{"node_idx_offset":15831231,"num_nodes":528834},"movie-any-new-review:Train":{"node_idx_offset":4296557,"num_nodes":1296909},"reviewer-distinct-movies:Train":{"node_idx_offset":25049436,"num_nodes":461291},"reviewer-rating-sum:Train":{"node_idx_offset":28278473,"num_nodes":461291},"reviewer-long-review-writer:Train":{"node_idx_offset":25972018,"num_nodes":461291},"reviewer-churn-8x:Train":{"node_idx_offset":24281021,"num_nodes":768415},"movie-unique-reviewers:Train":{"node_idx_offset":16360065,"num_nodes":528834},"reviewer-time-until-next-8x:Train":{"node_idx_offset":34889708,"num_nodes":358789},"movie-review-length-change:Train":{"node_idx_offset":14289775,"num_nodes":372863},"reviewer-verified-ratio:Train":{"node_idx_offset":36171070,"num_nodes":461291},"movie-all-verified:Train":{"node_idx_offset":3767723,"num_nodes":528834},"reviewer-min-rating:Train":{"node_idx_offset":27817182,"num_nodes":461291},"movie-time-until-next-4x:Train":{"node_idx_offset":14662638,"num_nodes":372031},"movie-min-rating:Train":{"node_idx_offset":10360058,"num_nodes":528834},"reviewer-will-review-movie:Train":{"node_idx_offset":36632361,"num_nodes":2049645},"movies:Db":{"node_idx_offset":0,"num_nodes":60175},"reviewer-churn:Train":{"node_idx_offset":18714642,"num_nodes":2049644},"movie-rating-volatility:Train":{"node_idx_offset":11790589,"num_nodes":270900},"reviewer-return:Train":{"node_idx_offset":28739764,"num_nodes":1118673},"reviewer-long-writer:Train":{"node_idx_offset":26433309,"num_nodes":461291},"reviewer-return-6x:Train":{"node_idx_offset":30952077,"num_nodes":291522},"movie-popular-next-window:Train":{"node_idx_offset":10888892,"num_nodes":528834},"movie-churn-4x:Train":{"node_idx_offset":6890358,"num_nodes":618005},"reviewer-mean-rating:Train":{"node_idx_offset":27355891,"num_nodes":461291},"movie-rating-trend:Train":{"node_idx_offset":11417726,"num_nodes":372863},"reviewer-verified-only:Train":{"node_idx_offset":35709779,"num_nodes":461291},"reviewer-max-rating:Train":{"node_idx_offset":26894600,"num_nodes":461291},"movie-churn-8x:Train":{"node_idx_offset":7909263,"num_nodes":335459},"movie-time-until-next-6x:Train":{"node_idx_offset":15034669,"num_nodes":267731},"reviewer-return-8x:Train":{"node_idx_offset":31243599,"num_nodes":229889},"reviewer-time-until-next-6x:Train":{"node_idx_offset":34526018,"num_nodes":363690},"movie-mean-rating:Train":{"node_idx_offset":9831224,"num_nodes":528834},"movie-top-review-volume:Train":{"node_idx_offset":15302400,"num_nodes":528831},"movie-return:Train":{"node_idx_offset":12061489,"num_nodes":572378},"movie-verified-count:Train":{"node_idx_offset":16888899,"num_nodes":528834},"movie-return-8x:Train":{"node_idx_offset":12922770,"num_nodes":70113},"reviews:Db":{"node_idx_offset":357704,"num_nodes":3410019},"reviewer-return-4x:Train":{"node_idx_offset":29858437,"num_nodes":567238},"reviewer-review-count:Train":{"node_idx_offset":31473488,"num_nodes":2049644},"reviewer-churn-6x:Train":{"node_idx_offset":23444627,"num_nodes":836394},"reviewer-top-activity:Train":{"node_idx_offset":35248497,"num_nodes":461282},"movie-low-rating:Train":{"node_idx_offset":8773556,"num_nodes":528834},"movie-long-review:Train":{"node_idx_offset":8244722,"num_nodes":528834},"movie-low-rating-event:Train":{"node_idx_offset":9302390,"num_nodes":528834},"reviewer-return-5x:Train":{"node_idx_offset":30425675,"num_nodes":526402},"movie-review-count:Train":{"node_idx_offset":12992883,"num_nodes":1296892},"movie-churn:Train":{"node_idx_offset":5593466,"num_nodes":1296892},"movie-will-be-reviewed:Train":{"node_idx_offset":17417733,"num_nodes":1296909},"movie-return-6x:Train":{"node_idx_offset":12819952,"num_nodes":102818},"movie-churn-6x:Train":{"node_idx_offset":7508363,"num_nodes":400900},"reviewer-harsh-critic:Train":{"node_idx_offset":25510727,"num_nodes":461291},"reviewer-time-until-next-4x:Train":{"node_idx_offset":33523132,"num_nodes":493990},"reviewer-churn-5x:Train":{"node_idx_offset":22122265,"num_nodes":1322362},"reviewers:Db":{"node_idx_offset":60175,"num_nodes":297529},"movie-return-4x:Train":{"node_idx_offset":12633867,"num_nodes":186085}}
|
|
|
|
|
|
join-amazon-movies/text.json
DELETED
|
The diff for this file is too large to render.
See raw diff
|
|
|
join-amazon-movies/text_emb_all-MiniLM-L12-v2.bin
DELETED
|
@@ -1,3 +0,0 @@
|
|
| 1 |
-
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:2d9f2bb1961bca4576b4324e20981af53a2c2b87e13a1619de7733e6bd41ac3e
|
| 3 |
-
size 239476224
|
|
|
|
|
|
|
|
|
|
|
|
join-amazon-sports/column_index.json
DELETED
|
@@ -1 +0,0 @@
|
|
| 1 |
-
{"timestamp of product-min-rating":119764,"reviewed_next of product-will-be-reviewed":353496,"reviewer_id of reviewer-review-count":353482,"timestamp of cold-start-product-repeat-long":32,"timestamp of product-low-rating":352802,"timestamp of reviewer-churn":352841,"will_get_verified of cold-start-product-verified":21,"reviewer_id of reviewer-avg-review-length":71,"reviewer_returns of reviewer-returns":352806,"all_verified_reviewer of reviewer-verified-only":352857,"product_id of product-popular-next-window":353486,"avg_review_len of product-avg-review-length":16,"timestamp of cold-start-product-verified":20,"rating_trend_up of reviewer-rating-trend":352849,"product_id of product-verified-1star-rare":353502,"timestamp of cold-start-product-immediate":44,"low_rating_event of product-low-rating-event":352837,"product_id of cold-start-product-verified":19,"reviewer_id of reviewer-total-review-len":352852,"timestamp of product-review-length-change":352866,"product_id of cold-start-product-immediate":43,"will_return_immediate of cold-start-reviewer-immediate":353456,"max_review_len of product-max-review-length":52,"timestamp of reviewer-max-rating":352886,"total_len of reviewer-total-review-length":353499,"timestamp of product-rating-volatility":352822,"reviewer_id of cold-start-reviewer-verified":47,"timestamp of reviews":352894,"will_post_again_verified of cold-start-reviewer-verified":49,"timestamp of reviewer-1star-review-rare":352813,"timestamp of reviewer-premium-product-rare":64,"timestamp of reviewer-avg-review-length":73,"has_1star_review of product-1star-review-rare":353460,"product_id of product-all-verified":352872,"long_writer of reviewer-long-writer":119767,"product_id of product-returns":353510,"timestamp of product-multi-1star-rare":353479,"product_id of product-low-rating":352800,"timestamp of reviewer-verified-1star-rare":3,"timestamp of product-will-be-reviewed":353495,"product_id of product-verified-share":352880,"timestamp of product-returns":353511,"timestamp of product-review-count":61,"reviewer_id of reviewers":119769,"timestamp of cold-start-reviewer-repeat":352877,"product_id of product-verified-count":11,"timestamp of product-verified-1star-rare":353503,"timestamp of cold-start-reviewer-multi-return":352829,"pred_rating of product-mean-rating":353523,"price of products":119756,"timestamp of product-premium-review-rare":353515,"rating_sum of product-total-rating-sum":8,"predict_product_review_count of product-review-count":60,"reviewer_min_rating of reviewer-min-rating":352845,"timestamp of reviewer-rating-trend":352850,"timestamp of reviewer-total-review-length":353500,"long_review of product-long-review":353519,"has_3plus_verified of reviewer-multi-verified-rare":29,"timestamp of product-total-rating-sum":9,"title of products":75,"avg_rating of products":119759,"timestamp of cold-start-product-repeat-review":352825,"timestamp of product-top-rated":37,"has_1star_review of reviewer-1star-review-rare":352814,"timestamp of product-any-new-review":352809,"timestamp of reviewer-harsh-critic":352818,"reviewer_id of cold-start-reviewer-repeat":352876,"timestamp of product-verified-share":352882,"rating of reviews":352893,"review_len of reviews":353452,"max_review_len of product-max-review-len":353471,"reviewer_id of cold-start-reviewer-immediate":353454,"timestamp of product-max-review-len":353472,"distinct_products_reviewed of reviewer-distinct-products":353475,"has_2plus_1star of product-multi-1star-rare":353480,"verbose_reviewer of reviewer-long-review-writer":353491,"has_verified_1star of product-verified-1star-rare":353504,"product_id of product-mean-rating":353522,"product_id of product-review-count":59,"reviewer_id of reviewer-verified-1star-rare":1,"category of products":119757,"reviews_next of reviewer-will-review-sports":352870,"reviewer_id of reviewer-total-review-length":353498,"timestamp of product-all-verified":352874,"reviewer_total_len of reviewer-total-review-len":352853,"reviewer_id of reviewer-verified-ratio":353466,"will_return of cold-start-reviewer-repeat":352878,"timestamp of reviewer-rating-sum":353464,"product_id of product-verified-review-rare":55,"product_id of product-top-review-volume":352860,"brand of products":101361,"timestamp of product-popular-next-window":353488,"all_verified of product-all-verified":352873,"reviewer_name of reviewers":119770,"reviewer_id of reviewer-long-review-writer":353490,"reviewer_range of product-unique-reviewers":352833,"product_id of products":74,"timestamp of reviewer-total-review-len":352854,"predict_product_churn of product-churn":353508,"reviewer_id of reviewer-returns":352804,"has_premium_review of product-premium-review-rare":353516,"reviewer_id of reviewer-churn":352840,"timestamp of reviewer-will-review-sports":352869,"has_premium_review of reviewer-premium-product-rare":65,"product_id of cold-start-product-repeat-review":352824,"reviewer_id of reviewer-verified-only":352856,"reviewer_max_rating of reviewer-max-rating":352885,"timestamp of cold-start-reviewer-immediate":353455,"n_reviews of products":119760,"timestamp of cold-start-reviewer-verified":48,"min_rating of product-min-rating":119763,"rating_sum of reviewer-rating-sum":353463,"product_id of product-rating-trend":353526,"predict_reviewer_review_count of reviewer-review-count":353483,"timestamp of reviewer-multi-verified-rare":28,"reviewer_id of reviewer-max-review-len":352796,"timestamp of product-avg-review-length":17,"reviewer_id of reviewer-long-writer":119766,"will_get_repeat_3w of cold-start-product-repeat-long":33,"has_verified_review of product-verified-review-rare":57,"will_return_multi of cold-start-reviewer-multi-return":352830,"will_get_review_immediate of cold-start-product-immediate":45,"timestamp of product-verified-review-rare":56,"timestamp of product-low-rating-event":352838,"reviewer_id of reviewer-rating-trend":352848,"verified_rate of product-verified-share":352881,"reviewer_id of reviewer-max-rating":352884,"timestamp of reviewer-long-writer":119768,"product_id of product-low-rating-event":352836,"reviewer_id of reviewer-min-rating":352844,"timestamp of reviewer-max-review-len":352798,"book_has_review of product-any-new-review":352810,"has_verified_review of reviewer-verified-review-rare":69,"reviewer_id of reviewer-multi-verified-rare":27,"reviewer_id of reviewer-premium-product-rare":63,"top_review_volume of product-top-review-volume":352861,"reviewer_id of reviewer-mean-rating":352888,"product_id of reviews":352892,"product_id of product-1star-review-rare":353458,"reviewer_max_len of reviewer-max-review-len":352797,"reviewer_id of reviewer-rating-sum":353462,"product_id of cold-start-product-multi-return":23,"timestamp of product-1star-review-rare":353459,"timestamp of reviewer-distinct-products":353476,"product_id of product-multi-1star-rare":353478,"has_verified_1star of reviewer-verified-1star-rare":4,"product_id of cold-start-product-repeat-long":31,"reviewer_id of reviewer-will-review-sports":352868,"timestamp of product-max-review-length":53,"popular of product-popular-next-window":353487,"reviewer_id of reviewer-harsh-critic":352816,"timestamp of cold-start-product-multi-return":24,"timestamp of reviewer-long-review-writer":353492,"harsh_critic of reviewer-harsh-critic":352817,"pred_verified of reviewer-verified-ratio":353467,"timestamp of reviewer-review-count":353484,"product_id of product-max-review-length":51,"product_id of product-premium-review-rare":353514,"product_id of product-min-rating":119762,"product_id of product-long-review":353518,"reviewer_id of cold-start-reviewer-repeat-long":39,"rating_trend_up of product-rating-trend":353527,"reviewer_id of reviewer-distinct-products":353474,"will_get_repeat of cold-start-product-repeat-review":352826,"avg_review_len of reviewer-avg-review-length":72,"timestamp of product-top-review-volume":352862,"pred_rating of reviewer-mean-rating":352889,"product_id of product-top-rated":35,"review_len_delta of product-review-length-change":352865,"timestamp of reviewer-mean-rating":352890,"product_id of product-review-length-change":352864,"timestamp of reviewer-verified-ratio":353468,"product_id of product-total-rating-sum":6,"reviewer_id of reviews":352891,"timestamp of product-mean-rating":353524,"product_id of product-avg-review-length":15,"timestamp of product-long-review":353520,"timestamp of product-verified-count":13,"vote of reviews":352896,"product_id of product-churn":353506,"reviewer_id of reviewer-verified-review-rare":67,"timestamp of reviewer-returns":352805,"verified_count of product-verified-count":12,"product_id of product-rating-volatility":352820,"will_get_multi of cold-start-product-multi-return":25,"reviewer_id of cold-start-reviewer-multi-return":352828,"predict_reviewer_churn of reviewer-churn":352842,"product_id of product-unique-reviewers":352832,"timestamp of reviewer-verified-only":352858,"timestamp of reviewer-verified-review-rare":68,"reviewer_id of reviewer-1star-review-rare":352812,"timestamp of product-rating-trend":353528,"top_rated of product-top-rated":36,"low_rating of product-low-rating":352801,"verified of reviews":352895,"product_id of product-will-be-reviewed":353494,"product_id of product-max-review-len":353470,"will_return_3w of cold-start-reviewer-repeat-long":41,"product_returns of product-returns":353512,"timestamp of product-unique-reviewers":352834,"timestamp of cold-start-reviewer-repeat-long":40,"rating_std of product-rating-volatility":352821,"product_id of product-any-new-review":352808,"timestamp of reviewer-min-rating":352846,"timestamp of product-churn":353507}
|
|
|
|
|
|
join-amazon-sports/meta.json
DELETED
|
@@ -1,772 +0,0 @@
|
|
| 1 |
-
{
|
| 2 |
-
"files": {
|
| 3 |
-
"column_index": "column_index.json",
|
| 4 |
-
"nodes": "nodes.rkyv",
|
| 5 |
-
"offsets": "offsets.rkyv",
|
| 6 |
-
"p2f_adj": "p2f_adj.rkyv",
|
| 7 |
-
"table_info": "table_info.json",
|
| 8 |
-
"text": "text.json"
|
| 9 |
-
},
|
| 10 |
-
"format_version": 1,
|
| 11 |
-
"name": "join-amazon-sports",
|
| 12 |
-
"num_db_tables": 3,
|
| 13 |
-
"num_nodes": 57308571,
|
| 14 |
-
"num_task_tables": 63,
|
| 15 |
-
"num_text_strings": 353529,
|
| 16 |
-
"source": "stanford-star/the-join/join-amazon-sports",
|
| 17 |
-
"tasks": [
|
| 18 |
-
{
|
| 19 |
-
"entity_table": "products",
|
| 20 |
-
"kind": "forecast",
|
| 21 |
-
"name": "cold-start-product-immediate",
|
| 22 |
-
"splits": [
|
| 23 |
-
"train"
|
| 24 |
-
],
|
| 25 |
-
"target_col": "will_get_review_immediate",
|
| 26 |
-
"task_type": "binary_classification",
|
| 27 |
-
"time_col": "timestamp"
|
| 28 |
-
},
|
| 29 |
-
{
|
| 30 |
-
"entity_table": "products",
|
| 31 |
-
"kind": "forecast",
|
| 32 |
-
"name": "cold-start-product-multi-return",
|
| 33 |
-
"splits": [
|
| 34 |
-
"train"
|
| 35 |
-
],
|
| 36 |
-
"target_col": "will_get_multi",
|
| 37 |
-
"task_type": "binary_classification",
|
| 38 |
-
"time_col": "timestamp"
|
| 39 |
-
},
|
| 40 |
-
{
|
| 41 |
-
"entity_table": "products",
|
| 42 |
-
"kind": "forecast",
|
| 43 |
-
"name": "cold-start-product-repeat-long",
|
| 44 |
-
"splits": [
|
| 45 |
-
"train"
|
| 46 |
-
],
|
| 47 |
-
"target_col": "will_get_repeat_3w",
|
| 48 |
-
"task_type": "binary_classification",
|
| 49 |
-
"time_col": "timestamp"
|
| 50 |
-
},
|
| 51 |
-
{
|
| 52 |
-
"entity_table": "products",
|
| 53 |
-
"kind": "forecast",
|
| 54 |
-
"name": "cold-start-product-repeat-review",
|
| 55 |
-
"splits": [
|
| 56 |
-
"train"
|
| 57 |
-
],
|
| 58 |
-
"target_col": "will_get_repeat",
|
| 59 |
-
"task_type": "binary_classification",
|
| 60 |
-
"time_col": "timestamp"
|
| 61 |
-
},
|
| 62 |
-
{
|
| 63 |
-
"entity_table": "products",
|
| 64 |
-
"kind": "forecast",
|
| 65 |
-
"name": "cold-start-product-verified",
|
| 66 |
-
"splits": [
|
| 67 |
-
"train"
|
| 68 |
-
],
|
| 69 |
-
"target_col": "will_get_verified",
|
| 70 |
-
"task_type": "binary_classification",
|
| 71 |
-
"time_col": "timestamp"
|
| 72 |
-
},
|
| 73 |
-
{
|
| 74 |
-
"entity_table": "reviewers",
|
| 75 |
-
"kind": "forecast",
|
| 76 |
-
"name": "cold-start-reviewer-immediate",
|
| 77 |
-
"splits": [
|
| 78 |
-
"train"
|
| 79 |
-
],
|
| 80 |
-
"target_col": "will_return_immediate",
|
| 81 |
-
"task_type": "binary_classification",
|
| 82 |
-
"time_col": "timestamp"
|
| 83 |
-
},
|
| 84 |
-
{
|
| 85 |
-
"entity_table": "reviewers",
|
| 86 |
-
"kind": "forecast",
|
| 87 |
-
"name": "cold-start-reviewer-multi-return",
|
| 88 |
-
"splits": [
|
| 89 |
-
"train"
|
| 90 |
-
],
|
| 91 |
-
"target_col": "will_return_multi",
|
| 92 |
-
"task_type": "binary_classification",
|
| 93 |
-
"time_col": "timestamp"
|
| 94 |
-
},
|
| 95 |
-
{
|
| 96 |
-
"entity_table": "reviewers",
|
| 97 |
-
"kind": "forecast",
|
| 98 |
-
"name": "cold-start-reviewer-repeat",
|
| 99 |
-
"splits": [
|
| 100 |
-
"train"
|
| 101 |
-
],
|
| 102 |
-
"target_col": "will_return",
|
| 103 |
-
"task_type": "binary_classification",
|
| 104 |
-
"time_col": "timestamp"
|
| 105 |
-
},
|
| 106 |
-
{
|
| 107 |
-
"entity_table": "reviewers",
|
| 108 |
-
"kind": "forecast",
|
| 109 |
-
"name": "cold-start-reviewer-repeat-long",
|
| 110 |
-
"splits": [
|
| 111 |
-
"train"
|
| 112 |
-
],
|
| 113 |
-
"target_col": "will_return_3w",
|
| 114 |
-
"task_type": "binary_classification",
|
| 115 |
-
"time_col": "timestamp"
|
| 116 |
-
},
|
| 117 |
-
{
|
| 118 |
-
"entity_table": "reviewers",
|
| 119 |
-
"kind": "forecast",
|
| 120 |
-
"name": "cold-start-reviewer-verified",
|
| 121 |
-
"splits": [
|
| 122 |
-
"train"
|
| 123 |
-
],
|
| 124 |
-
"target_col": "will_post_again_verified",
|
| 125 |
-
"task_type": "binary_classification",
|
| 126 |
-
"time_col": "timestamp"
|
| 127 |
-
},
|
| 128 |
-
{
|
| 129 |
-
"entity_table": "products",
|
| 130 |
-
"kind": "forecast",
|
| 131 |
-
"name": "product-1star-review-rare",
|
| 132 |
-
"splits": [
|
| 133 |
-
"train"
|
| 134 |
-
],
|
| 135 |
-
"target_col": "has_1star_review",
|
| 136 |
-
"task_type": "binary_classification",
|
| 137 |
-
"time_col": "timestamp"
|
| 138 |
-
},
|
| 139 |
-
{
|
| 140 |
-
"entity_table": "products",
|
| 141 |
-
"kind": "forecast",
|
| 142 |
-
"name": "product-all-verified",
|
| 143 |
-
"splits": [
|
| 144 |
-
"train"
|
| 145 |
-
],
|
| 146 |
-
"target_col": "all_verified",
|
| 147 |
-
"task_type": "binary_classification",
|
| 148 |
-
"time_col": "timestamp"
|
| 149 |
-
},
|
| 150 |
-
{
|
| 151 |
-
"entity_table": "products",
|
| 152 |
-
"kind": "forecast",
|
| 153 |
-
"name": "product-any-new-review",
|
| 154 |
-
"splits": [
|
| 155 |
-
"train"
|
| 156 |
-
],
|
| 157 |
-
"target_col": "book_has_review",
|
| 158 |
-
"task_type": "binary_classification",
|
| 159 |
-
"time_col": "timestamp"
|
| 160 |
-
},
|
| 161 |
-
{
|
| 162 |
-
"entity_table": "products",
|
| 163 |
-
"kind": "forecast",
|
| 164 |
-
"name": "product-avg-review-length",
|
| 165 |
-
"splits": [
|
| 166 |
-
"train"
|
| 167 |
-
],
|
| 168 |
-
"target_col": "avg_review_len",
|
| 169 |
-
"task_type": "regression",
|
| 170 |
-
"time_col": "timestamp"
|
| 171 |
-
},
|
| 172 |
-
{
|
| 173 |
-
"entity_table": "products",
|
| 174 |
-
"kind": "forecast",
|
| 175 |
-
"name": "product-churn",
|
| 176 |
-
"splits": [
|
| 177 |
-
"train"
|
| 178 |
-
],
|
| 179 |
-
"target_col": "predict_product_churn",
|
| 180 |
-
"task_type": "binary_classification",
|
| 181 |
-
"time_col": "timestamp"
|
| 182 |
-
},
|
| 183 |
-
{
|
| 184 |
-
"entity_table": "products",
|
| 185 |
-
"kind": "forecast",
|
| 186 |
-
"name": "product-long-review",
|
| 187 |
-
"splits": [
|
| 188 |
-
"train"
|
| 189 |
-
],
|
| 190 |
-
"target_col": "long_review",
|
| 191 |
-
"task_type": "binary_classification",
|
| 192 |
-
"time_col": "timestamp"
|
| 193 |
-
},
|
| 194 |
-
{
|
| 195 |
-
"entity_table": "products",
|
| 196 |
-
"kind": "forecast",
|
| 197 |
-
"name": "product-low-rating",
|
| 198 |
-
"splits": [
|
| 199 |
-
"train"
|
| 200 |
-
],
|
| 201 |
-
"target_col": "low_rating",
|
| 202 |
-
"task_type": "binary_classification",
|
| 203 |
-
"time_col": "timestamp"
|
| 204 |
-
},
|
| 205 |
-
{
|
| 206 |
-
"entity_table": "products",
|
| 207 |
-
"kind": "forecast",
|
| 208 |
-
"name": "product-low-rating-event",
|
| 209 |
-
"splits": [
|
| 210 |
-
"train"
|
| 211 |
-
],
|
| 212 |
-
"target_col": "low_rating_event",
|
| 213 |
-
"task_type": "binary_classification",
|
| 214 |
-
"time_col": "timestamp"
|
| 215 |
-
},
|
| 216 |
-
{
|
| 217 |
-
"entity_table": "products",
|
| 218 |
-
"kind": "forecast",
|
| 219 |
-
"name": "product-max-review-len",
|
| 220 |
-
"splits": [
|
| 221 |
-
"train"
|
| 222 |
-
],
|
| 223 |
-
"target_col": "max_review_len",
|
| 224 |
-
"task_type": "regression",
|
| 225 |
-
"time_col": "timestamp"
|
| 226 |
-
},
|
| 227 |
-
{
|
| 228 |
-
"entity_table": "products",
|
| 229 |
-
"kind": "forecast",
|
| 230 |
-
"name": "product-max-review-length",
|
| 231 |
-
"splits": [
|
| 232 |
-
"train"
|
| 233 |
-
],
|
| 234 |
-
"target_col": "max_review_len",
|
| 235 |
-
"task_type": "regression",
|
| 236 |
-
"time_col": "timestamp"
|
| 237 |
-
},
|
| 238 |
-
{
|
| 239 |
-
"entity_table": "products",
|
| 240 |
-
"kind": "forecast",
|
| 241 |
-
"name": "product-mean-rating",
|
| 242 |
-
"splits": [
|
| 243 |
-
"train"
|
| 244 |
-
],
|
| 245 |
-
"target_col": "pred_rating",
|
| 246 |
-
"task_type": "regression",
|
| 247 |
-
"time_col": "timestamp"
|
| 248 |
-
},
|
| 249 |
-
{
|
| 250 |
-
"entity_table": "products",
|
| 251 |
-
"kind": "forecast",
|
| 252 |
-
"name": "product-min-rating",
|
| 253 |
-
"splits": [
|
| 254 |
-
"train"
|
| 255 |
-
],
|
| 256 |
-
"target_col": "min_rating",
|
| 257 |
-
"task_type": "regression",
|
| 258 |
-
"time_col": "timestamp"
|
| 259 |
-
},
|
| 260 |
-
{
|
| 261 |
-
"entity_table": "products",
|
| 262 |
-
"kind": "forecast",
|
| 263 |
-
"name": "product-multi-1star-rare",
|
| 264 |
-
"splits": [
|
| 265 |
-
"train"
|
| 266 |
-
],
|
| 267 |
-
"target_col": "has_2plus_1star",
|
| 268 |
-
"task_type": "binary_classification",
|
| 269 |
-
"time_col": "timestamp"
|
| 270 |
-
},
|
| 271 |
-
{
|
| 272 |
-
"entity_table": "products",
|
| 273 |
-
"kind": "forecast",
|
| 274 |
-
"name": "product-popular-next-window",
|
| 275 |
-
"splits": [
|
| 276 |
-
"train"
|
| 277 |
-
],
|
| 278 |
-
"target_col": "popular",
|
| 279 |
-
"task_type": "binary_classification",
|
| 280 |
-
"time_col": "timestamp"
|
| 281 |
-
},
|
| 282 |
-
{
|
| 283 |
-
"entity_table": "products",
|
| 284 |
-
"kind": "forecast",
|
| 285 |
-
"name": "product-premium-review-rare",
|
| 286 |
-
"splits": [
|
| 287 |
-
"train"
|
| 288 |
-
],
|
| 289 |
-
"target_col": "has_premium_review",
|
| 290 |
-
"task_type": "binary_classification",
|
| 291 |
-
"time_col": "timestamp"
|
| 292 |
-
},
|
| 293 |
-
{
|
| 294 |
-
"entity_table": "products",
|
| 295 |
-
"kind": "forecast",
|
| 296 |
-
"name": "product-rating-trend",
|
| 297 |
-
"splits": [
|
| 298 |
-
"train"
|
| 299 |
-
],
|
| 300 |
-
"target_col": "rating_trend_up",
|
| 301 |
-
"task_type": "binary_classification",
|
| 302 |
-
"time_col": "timestamp"
|
| 303 |
-
},
|
| 304 |
-
{
|
| 305 |
-
"entity_table": "products",
|
| 306 |
-
"kind": "forecast",
|
| 307 |
-
"name": "product-rating-volatility",
|
| 308 |
-
"splits": [
|
| 309 |
-
"train"
|
| 310 |
-
],
|
| 311 |
-
"target_col": "rating_std",
|
| 312 |
-
"task_type": "regression",
|
| 313 |
-
"time_col": "timestamp"
|
| 314 |
-
},
|
| 315 |
-
{
|
| 316 |
-
"entity_table": "products",
|
| 317 |
-
"kind": "forecast",
|
| 318 |
-
"name": "product-returns",
|
| 319 |
-
"splits": [
|
| 320 |
-
"train"
|
| 321 |
-
],
|
| 322 |
-
"target_col": "product_returns",
|
| 323 |
-
"task_type": "binary_classification",
|
| 324 |
-
"time_col": "timestamp"
|
| 325 |
-
},
|
| 326 |
-
{
|
| 327 |
-
"entity_table": "products",
|
| 328 |
-
"kind": "forecast",
|
| 329 |
-
"name": "product-review-count",
|
| 330 |
-
"splits": [
|
| 331 |
-
"train"
|
| 332 |
-
],
|
| 333 |
-
"target_col": "predict_product_review_count",
|
| 334 |
-
"task_type": "regression",
|
| 335 |
-
"time_col": "timestamp"
|
| 336 |
-
},
|
| 337 |
-
{
|
| 338 |
-
"entity_table": "products",
|
| 339 |
-
"kind": "forecast",
|
| 340 |
-
"name": "product-review-length-change",
|
| 341 |
-
"splits": [
|
| 342 |
-
"train"
|
| 343 |
-
],
|
| 344 |
-
"target_col": "review_len_delta",
|
| 345 |
-
"task_type": "regression",
|
| 346 |
-
"time_col": "timestamp"
|
| 347 |
-
},
|
| 348 |
-
{
|
| 349 |
-
"entity_table": "products",
|
| 350 |
-
"kind": "forecast",
|
| 351 |
-
"name": "product-top-rated",
|
| 352 |
-
"splits": [
|
| 353 |
-
"train"
|
| 354 |
-
],
|
| 355 |
-
"target_col": "top_rated",
|
| 356 |
-
"task_type": "binary_classification",
|
| 357 |
-
"time_col": "timestamp"
|
| 358 |
-
},
|
| 359 |
-
{
|
| 360 |
-
"entity_table": "products",
|
| 361 |
-
"kind": "forecast",
|
| 362 |
-
"name": "product-top-review-volume",
|
| 363 |
-
"splits": [
|
| 364 |
-
"train"
|
| 365 |
-
],
|
| 366 |
-
"target_col": "top_review_volume",
|
| 367 |
-
"task_type": "binary_classification",
|
| 368 |
-
"time_col": "timestamp"
|
| 369 |
-
},
|
| 370 |
-
{
|
| 371 |
-
"entity_table": "products",
|
| 372 |
-
"kind": "forecast",
|
| 373 |
-
"name": "product-total-rating-sum",
|
| 374 |
-
"splits": [
|
| 375 |
-
"train"
|
| 376 |
-
],
|
| 377 |
-
"target_col": "rating_sum",
|
| 378 |
-
"task_type": "regression",
|
| 379 |
-
"time_col": "timestamp"
|
| 380 |
-
},
|
| 381 |
-
{
|
| 382 |
-
"entity_table": "products",
|
| 383 |
-
"kind": "forecast",
|
| 384 |
-
"name": "product-unique-reviewers",
|
| 385 |
-
"splits": [
|
| 386 |
-
"train"
|
| 387 |
-
],
|
| 388 |
-
"target_col": "reviewer_range",
|
| 389 |
-
"task_type": "regression",
|
| 390 |
-
"time_col": "timestamp"
|
| 391 |
-
},
|
| 392 |
-
{
|
| 393 |
-
"entity_table": "products",
|
| 394 |
-
"kind": "forecast",
|
| 395 |
-
"name": "product-verified-1star-rare",
|
| 396 |
-
"splits": [
|
| 397 |
-
"train"
|
| 398 |
-
],
|
| 399 |
-
"target_col": "has_verified_1star",
|
| 400 |
-
"task_type": "binary_classification",
|
| 401 |
-
"time_col": "timestamp"
|
| 402 |
-
},
|
| 403 |
-
{
|
| 404 |
-
"entity_table": "products",
|
| 405 |
-
"kind": "forecast",
|
| 406 |
-
"name": "product-verified-count",
|
| 407 |
-
"splits": [
|
| 408 |
-
"train"
|
| 409 |
-
],
|
| 410 |
-
"target_col": "verified_count",
|
| 411 |
-
"task_type": "regression",
|
| 412 |
-
"time_col": "timestamp"
|
| 413 |
-
},
|
| 414 |
-
{
|
| 415 |
-
"entity_table": "products",
|
| 416 |
-
"kind": "forecast",
|
| 417 |
-
"name": "product-verified-review-rare",
|
| 418 |
-
"splits": [
|
| 419 |
-
"train"
|
| 420 |
-
],
|
| 421 |
-
"target_col": "has_verified_review",
|
| 422 |
-
"task_type": "binary_classification",
|
| 423 |
-
"time_col": "timestamp"
|
| 424 |
-
},
|
| 425 |
-
{
|
| 426 |
-
"entity_table": "products",
|
| 427 |
-
"kind": "forecast",
|
| 428 |
-
"name": "product-verified-share",
|
| 429 |
-
"splits": [
|
| 430 |
-
"train"
|
| 431 |
-
],
|
| 432 |
-
"target_col": "verified_rate",
|
| 433 |
-
"task_type": "regression",
|
| 434 |
-
"time_col": "timestamp"
|
| 435 |
-
},
|
| 436 |
-
{
|
| 437 |
-
"entity_table": "products",
|
| 438 |
-
"kind": "forecast",
|
| 439 |
-
"name": "product-will-be-reviewed",
|
| 440 |
-
"splits": [
|
| 441 |
-
"train"
|
| 442 |
-
],
|
| 443 |
-
"target_col": "reviewed_next",
|
| 444 |
-
"task_type": "binary_classification",
|
| 445 |
-
"time_col": "timestamp"
|
| 446 |
-
},
|
| 447 |
-
{
|
| 448 |
-
"entity_table": "products",
|
| 449 |
-
"kind": "autocomplete",
|
| 450 |
-
"name": "products-avg_rating",
|
| 451 |
-
"splits": [],
|
| 452 |
-
"target_col": "avg_rating",
|
| 453 |
-
"task_type": "regression",
|
| 454 |
-
"time_col": null
|
| 455 |
-
},
|
| 456 |
-
{
|
| 457 |
-
"entity_table": "products",
|
| 458 |
-
"kind": "autocomplete",
|
| 459 |
-
"name": "products-n_reviews",
|
| 460 |
-
"splits": [],
|
| 461 |
-
"target_col": "n_reviews",
|
| 462 |
-
"task_type": "regression",
|
| 463 |
-
"time_col": null
|
| 464 |
-
},
|
| 465 |
-
{
|
| 466 |
-
"entity_table": "products",
|
| 467 |
-
"kind": "autocomplete",
|
| 468 |
-
"name": "products-price",
|
| 469 |
-
"splits": [],
|
| 470 |
-
"target_col": "price",
|
| 471 |
-
"task_type": "regression",
|
| 472 |
-
"time_col": null
|
| 473 |
-
},
|
| 474 |
-
{
|
| 475 |
-
"entity_table": "reviewers",
|
| 476 |
-
"kind": "forecast",
|
| 477 |
-
"name": "reviewer-1star-review-rare",
|
| 478 |
-
"splits": [
|
| 479 |
-
"train"
|
| 480 |
-
],
|
| 481 |
-
"target_col": "has_1star_review",
|
| 482 |
-
"task_type": "binary_classification",
|
| 483 |
-
"time_col": "timestamp"
|
| 484 |
-
},
|
| 485 |
-
{
|
| 486 |
-
"entity_table": "reviewers",
|
| 487 |
-
"kind": "forecast",
|
| 488 |
-
"name": "reviewer-avg-review-length",
|
| 489 |
-
"splits": [
|
| 490 |
-
"train"
|
| 491 |
-
],
|
| 492 |
-
"target_col": "avg_review_len",
|
| 493 |
-
"task_type": "regression",
|
| 494 |
-
"time_col": "timestamp"
|
| 495 |
-
},
|
| 496 |
-
{
|
| 497 |
-
"entity_table": "reviewers",
|
| 498 |
-
"kind": "forecast",
|
| 499 |
-
"name": "reviewer-churn",
|
| 500 |
-
"splits": [
|
| 501 |
-
"train"
|
| 502 |
-
],
|
| 503 |
-
"target_col": "predict_reviewer_churn",
|
| 504 |
-
"task_type": "binary_classification",
|
| 505 |
-
"time_col": "timestamp"
|
| 506 |
-
},
|
| 507 |
-
{
|
| 508 |
-
"entity_table": "reviewers",
|
| 509 |
-
"kind": "forecast",
|
| 510 |
-
"name": "reviewer-distinct-products",
|
| 511 |
-
"splits": [
|
| 512 |
-
"train"
|
| 513 |
-
],
|
| 514 |
-
"target_col": "distinct_products_reviewed",
|
| 515 |
-
"task_type": "regression",
|
| 516 |
-
"time_col": "timestamp"
|
| 517 |
-
},
|
| 518 |
-
{
|
| 519 |
-
"entity_table": "reviewers",
|
| 520 |
-
"kind": "forecast",
|
| 521 |
-
"name": "reviewer-harsh-critic",
|
| 522 |
-
"splits": [
|
| 523 |
-
"train"
|
| 524 |
-
],
|
| 525 |
-
"target_col": "harsh_critic",
|
| 526 |
-
"task_type": "binary_classification",
|
| 527 |
-
"time_col": "timestamp"
|
| 528 |
-
},
|
| 529 |
-
{
|
| 530 |
-
"entity_table": "reviewers",
|
| 531 |
-
"kind": "forecast",
|
| 532 |
-
"name": "reviewer-long-review-writer",
|
| 533 |
-
"splits": [
|
| 534 |
-
"train"
|
| 535 |
-
],
|
| 536 |
-
"target_col": "verbose_reviewer",
|
| 537 |
-
"task_type": "binary_classification",
|
| 538 |
-
"time_col": "timestamp"
|
| 539 |
-
},
|
| 540 |
-
{
|
| 541 |
-
"entity_table": "reviewers",
|
| 542 |
-
"kind": "forecast",
|
| 543 |
-
"name": "reviewer-long-writer",
|
| 544 |
-
"splits": [
|
| 545 |
-
"train"
|
| 546 |
-
],
|
| 547 |
-
"target_col": "long_writer",
|
| 548 |
-
"task_type": "binary_classification",
|
| 549 |
-
"time_col": "timestamp"
|
| 550 |
-
},
|
| 551 |
-
{
|
| 552 |
-
"entity_table": "reviewers",
|
| 553 |
-
"kind": "forecast",
|
| 554 |
-
"name": "reviewer-max-rating",
|
| 555 |
-
"splits": [
|
| 556 |
-
"train"
|
| 557 |
-
],
|
| 558 |
-
"target_col": "reviewer_max_rating",
|
| 559 |
-
"task_type": "regression",
|
| 560 |
-
"time_col": "timestamp"
|
| 561 |
-
},
|
| 562 |
-
{
|
| 563 |
-
"entity_table": "reviewers",
|
| 564 |
-
"kind": "forecast",
|
| 565 |
-
"name": "reviewer-max-review-len",
|
| 566 |
-
"splits": [
|
| 567 |
-
"train"
|
| 568 |
-
],
|
| 569 |
-
"target_col": "reviewer_max_len",
|
| 570 |
-
"task_type": "regression",
|
| 571 |
-
"time_col": "timestamp"
|
| 572 |
-
},
|
| 573 |
-
{
|
| 574 |
-
"entity_table": "reviewers",
|
| 575 |
-
"kind": "forecast",
|
| 576 |
-
"name": "reviewer-mean-rating",
|
| 577 |
-
"splits": [
|
| 578 |
-
"train"
|
| 579 |
-
],
|
| 580 |
-
"target_col": "pred_rating",
|
| 581 |
-
"task_type": "regression",
|
| 582 |
-
"time_col": "timestamp"
|
| 583 |
-
},
|
| 584 |
-
{
|
| 585 |
-
"entity_table": "reviewers",
|
| 586 |
-
"kind": "forecast",
|
| 587 |
-
"name": "reviewer-min-rating",
|
| 588 |
-
"splits": [
|
| 589 |
-
"train"
|
| 590 |
-
],
|
| 591 |
-
"target_col": "reviewer_min_rating",
|
| 592 |
-
"task_type": "regression",
|
| 593 |
-
"time_col": "timestamp"
|
| 594 |
-
},
|
| 595 |
-
{
|
| 596 |
-
"entity_table": "reviewers",
|
| 597 |
-
"kind": "forecast",
|
| 598 |
-
"name": "reviewer-multi-verified-rare",
|
| 599 |
-
"splits": [
|
| 600 |
-
"train"
|
| 601 |
-
],
|
| 602 |
-
"target_col": "has_3plus_verified",
|
| 603 |
-
"task_type": "binary_classification",
|
| 604 |
-
"time_col": "timestamp"
|
| 605 |
-
},
|
| 606 |
-
{
|
| 607 |
-
"entity_table": "reviewers",
|
| 608 |
-
"kind": "forecast",
|
| 609 |
-
"name": "reviewer-premium-product-rare",
|
| 610 |
-
"splits": [
|
| 611 |
-
"train"
|
| 612 |
-
],
|
| 613 |
-
"target_col": "has_premium_review",
|
| 614 |
-
"task_type": "binary_classification",
|
| 615 |
-
"time_col": "timestamp"
|
| 616 |
-
},
|
| 617 |
-
{
|
| 618 |
-
"entity_table": "reviewers",
|
| 619 |
-
"kind": "forecast",
|
| 620 |
-
"name": "reviewer-rating-sum",
|
| 621 |
-
"splits": [
|
| 622 |
-
"train"
|
| 623 |
-
],
|
| 624 |
-
"target_col": "rating_sum",
|
| 625 |
-
"task_type": "regression",
|
| 626 |
-
"time_col": "timestamp"
|
| 627 |
-
},
|
| 628 |
-
{
|
| 629 |
-
"entity_table": "reviewers",
|
| 630 |
-
"kind": "forecast",
|
| 631 |
-
"name": "reviewer-rating-trend",
|
| 632 |
-
"splits": [
|
| 633 |
-
"train"
|
| 634 |
-
],
|
| 635 |
-
"target_col": "rating_trend_up",
|
| 636 |
-
"task_type": "binary_classification",
|
| 637 |
-
"time_col": "timestamp"
|
| 638 |
-
},
|
| 639 |
-
{
|
| 640 |
-
"entity_table": "reviewers",
|
| 641 |
-
"kind": "forecast",
|
| 642 |
-
"name": "reviewer-returns",
|
| 643 |
-
"splits": [
|
| 644 |
-
"train"
|
| 645 |
-
],
|
| 646 |
-
"target_col": "reviewer_returns",
|
| 647 |
-
"task_type": "binary_classification",
|
| 648 |
-
"time_col": "timestamp"
|
| 649 |
-
},
|
| 650 |
-
{
|
| 651 |
-
"entity_table": "reviewers",
|
| 652 |
-
"kind": "forecast",
|
| 653 |
-
"name": "reviewer-review-count",
|
| 654 |
-
"splits": [
|
| 655 |
-
"train"
|
| 656 |
-
],
|
| 657 |
-
"target_col": "predict_reviewer_review_count",
|
| 658 |
-
"task_type": "regression",
|
| 659 |
-
"time_col": "timestamp"
|
| 660 |
-
},
|
| 661 |
-
{
|
| 662 |
-
"entity_table": "reviewers",
|
| 663 |
-
"kind": "forecast",
|
| 664 |
-
"name": "reviewer-total-review-len",
|
| 665 |
-
"splits": [
|
| 666 |
-
"train"
|
| 667 |
-
],
|
| 668 |
-
"target_col": "reviewer_total_len",
|
| 669 |
-
"task_type": "regression",
|
| 670 |
-
"time_col": "timestamp"
|
| 671 |
-
},
|
| 672 |
-
{
|
| 673 |
-
"entity_table": "reviewers",
|
| 674 |
-
"kind": "forecast",
|
| 675 |
-
"name": "reviewer-total-review-length",
|
| 676 |
-
"splits": [
|
| 677 |
-
"train"
|
| 678 |
-
],
|
| 679 |
-
"target_col": "total_len",
|
| 680 |
-
"task_type": "regression",
|
| 681 |
-
"time_col": "timestamp"
|
| 682 |
-
},
|
| 683 |
-
{
|
| 684 |
-
"entity_table": "reviewers",
|
| 685 |
-
"kind": "forecast",
|
| 686 |
-
"name": "reviewer-verified-1star-rare",
|
| 687 |
-
"splits": [
|
| 688 |
-
"train"
|
| 689 |
-
],
|
| 690 |
-
"target_col": "has_verified_1star",
|
| 691 |
-
"task_type": "binary_classification",
|
| 692 |
-
"time_col": "timestamp"
|
| 693 |
-
},
|
| 694 |
-
{
|
| 695 |
-
"entity_table": "reviewers",
|
| 696 |
-
"kind": "forecast",
|
| 697 |
-
"name": "reviewer-verified-only",
|
| 698 |
-
"splits": [
|
| 699 |
-
"train"
|
| 700 |
-
],
|
| 701 |
-
"target_col": "all_verified_reviewer",
|
| 702 |
-
"task_type": "binary_classification",
|
| 703 |
-
"time_col": "timestamp"
|
| 704 |
-
},
|
| 705 |
-
{
|
| 706 |
-
"entity_table": "reviewers",
|
| 707 |
-
"kind": "forecast",
|
| 708 |
-
"name": "reviewer-verified-ratio",
|
| 709 |
-
"splits": [
|
| 710 |
-
"train"
|
| 711 |
-
],
|
| 712 |
-
"target_col": "pred_verified",
|
| 713 |
-
"task_type": "binary_classification",
|
| 714 |
-
"time_col": "timestamp"
|
| 715 |
-
},
|
| 716 |
-
{
|
| 717 |
-
"entity_table": "reviewers",
|
| 718 |
-
"kind": "forecast",
|
| 719 |
-
"name": "reviewer-verified-review-rare",
|
| 720 |
-
"splits": [
|
| 721 |
-
"train"
|
| 722 |
-
],
|
| 723 |
-
"target_col": "has_verified_review",
|
| 724 |
-
"task_type": "binary_classification",
|
| 725 |
-
"time_col": "timestamp"
|
| 726 |
-
},
|
| 727 |
-
{
|
| 728 |
-
"entity_table": "reviewers",
|
| 729 |
-
"kind": "forecast",
|
| 730 |
-
"name": "reviewer-will-review-sports",
|
| 731 |
-
"splits": [
|
| 732 |
-
"train"
|
| 733 |
-
],
|
| 734 |
-
"target_col": "reviews_next",
|
| 735 |
-
"task_type": "binary_classification",
|
| 736 |
-
"time_col": "timestamp"
|
| 737 |
-
},
|
| 738 |
-
{
|
| 739 |
-
"entity_table": "reviews",
|
| 740 |
-
"kind": "autocomplete",
|
| 741 |
-
"name": "reviews-rating",
|
| 742 |
-
"splits": [],
|
| 743 |
-
"target_col": "rating",
|
| 744 |
-
"task_type": "regression",
|
| 745 |
-
"time_col": null
|
| 746 |
-
},
|
| 747 |
-
{
|
| 748 |
-
"entity_table": "reviews",
|
| 749 |
-
"kind": "autocomplete",
|
| 750 |
-
"name": "reviews-review_len",
|
| 751 |
-
"splits": [],
|
| 752 |
-
"target_col": "review_len",
|
| 753 |
-
"task_type": "regression",
|
| 754 |
-
"time_col": null
|
| 755 |
-
},
|
| 756 |
-
{
|
| 757 |
-
"entity_table": "reviews",
|
| 758 |
-
"kind": "autocomplete",
|
| 759 |
-
"name": "reviews-verified",
|
| 760 |
-
"splits": [],
|
| 761 |
-
"target_col": "verified",
|
| 762 |
-
"task_type": "binary_classification",
|
| 763 |
-
"time_col": null
|
| 764 |
-
}
|
| 765 |
-
],
|
| 766 |
-
"text_embeddings": {
|
| 767 |
-
"all-MiniLM-L12-v2": {
|
| 768 |
-
"file": "text_emb_all-MiniLM-L12-v2.bin",
|
| 769 |
-
"d_text": 384
|
| 770 |
-
}
|
| 771 |
-
}
|
| 772 |
-
}
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
join-amazon-sports/nodes.rkyv
DELETED
|
@@ -1,3 +0,0 @@
|
|
| 1 |
-
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:fcff4057bb1b179c54eebf3d2bd5535c406c623bf2b48abdbc8a8a1374871dce
|
| 3 |
-
size 14416374960
|
|
|
|
|
|
|
|
|
|
|
|
join-amazon-sports/offsets.rkyv
DELETED
|
@@ -1,3 +0,0 @@
|
|
| 1 |
-
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:d05212990a9c254268e0f0503aa358b1ac0fae3342bcdb92622a8bdb51e9237a
|
| 3 |
-
size 458468592
|
|
|
|
|
|
|
|
|
|
|
|
join-amazon-sports/p2f_adj.rkyv
DELETED
|
@@ -1,3 +0,0 @@
|
|
| 1 |
-
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:af51ed26cb2904468296b1f88ea92c3f4cccb04e667caf2564d9f4a50c17b9b2
|
| 3 |
-
size 2111164696
|
|
|
|
|
|
|
|
|
|
|
|
join-amazon-sports/table_info.json
DELETED
|
@@ -1 +0,0 @@
|
|
| 1 |
-
{"product-will-be-reviewed:Train":{"node_idx_offset":29606293,"num_nodes":1464755},"cold-start-reviewer-immediate:Train":{"node_idx_offset":3777834,"num_nodes":301532},"product-top-rated:Train":{"node_idx_offset":22665915,"num_nodes":668470},"reviewer-rating-sum:Train":{"node_idx_offset":44223466,"num_nodes":411270},"product-low-rating:Train":{"node_idx_offset":11685139,"num_nodes":668492},"reviewer-max-rating:Train":{"node_idx_offset":37852796,"num_nodes":411270},"product-review-count:Train":{"node_idx_offset":20724814,"num_nodes":1464679},"product-churn:Train":{"node_idx_offset":9551968,"num_nodes":1464679},"cold-start-reviewer-repeat-long:Train":{"node_idx_offset":4682430,"num_nodes":301532},"reviewer-distinct-products:Train":{"node_idx_offset":36207716,"num_nodes":411270},"product-rating-volatility:Train":{"node_idx_offset":19770475,"num_nodes":350304},"reviewer-will-review-sports:Train":{"node_idx_offset":54945756,"num_nodes":2362815},"product-verified-share:Train":{"node_idx_offset":28937801,"num_nodes":668492},"cold-start-product-repeat-review:Train":{"node_idx_offset":3577530,"num_nodes":100152},"reviewer-premium-product-rare:Train":{"node_idx_offset":41860671,"num_nodes":2362795},"product-review-length-change:Train":{"node_idx_offset":22189493,"num_nodes":476422},"product-long-review:Train":{"node_idx_offset":11016647,"num_nodes":668492},"reviewer-total-review-len:Train":{"node_idx_offset":48575086,"num_nodes":411270},"product-max-review-len:Train":{"node_idx_offset":13022123,"num_nodes":668492},"reviewer-review-count:Train":{"node_idx_offset":46212483,"num_nodes":2362603},"reviews:Db":{"node_idx_offset":437134,"num_nodes":2839940},"product-unique-reviewers:Train":{"node_idx_offset":24671347,"num_nodes":668492},"reviewer-avg-review-length:Train":{"node_idx_offset":33433843,"num_nodes":411270},"product-low-rating-event:Train":{"node_idx_offset":12353631,"num_nodes":668492},"reviewer-multi-verified-rare:Train":{"node_idx_offset":39497876,"num_nodes":2362795},"product-top-review-volume:Train":{"node_idx_offset":23334385,"num_nodes":668470},"products:Db":{"node_idx_offset":0,"num_nodes":104687},"product-verified-count:Train":{"node_idx_offset":26804574,"num_nodes":668492},"reviewer-verified-ratio:Train":{"node_idx_offset":52171691,"num_nodes":411270},"reviewer-max-review-len:Train":{"node_idx_offset":38264066,"num_nodes":411270},"product-popular-next-window:Train":{"node_idx_offset":17160826,"num_nodes":668492},"reviewer-min-rating:Train":{"node_idx_offset":39086606,"num_nodes":411270},"product-returns:Train":{"node_idx_offset":20120779,"num_nodes":604035},"cold-start-reviewer-verified:Train":{"node_idx_offset":4983962,"num_nodes":301532},"product-verified-review-rare:Train":{"node_idx_offset":27473066,"num_nodes":1464735},"cold-start-product-repeat-long:Train":{"node_idx_offset":3477378,"num_nodes":100152},"reviewer-churn:Train":{"node_idx_offset":33845113,"num_nodes":2362603},"cold-start-product-verified:Train":{"node_idx_offset":3677682,"num_nodes":100152},"reviewers:Db":{"node_idx_offset":104687,"num_nodes":332447},"product-all-verified:Train":{"node_idx_offset":6750229,"num_nodes":668492},"cold-start-reviewer-multi-return:Train":{"node_idx_offset":4079366,"num_nodes":301532},"cold-start-product-multi-return:Train":{"node_idx_offset":3377226,"num_nodes":100152},"reviewer-verified-1star-rare:Train":{"node_idx_offset":49397626,"num_nodes":2362795},"product-avg-review-length:Train":{"node_idx_offset":8883476,"num_nodes":668492},"product-rating-trend:Train":{"node_idx_offset":19294053,"num_nodes":476422},"product-min-rating:Train":{"node_idx_offset":15027599,"num_nodes":668492},"reviewer-returns:Train":{"node_idx_offset":44848001,"num_nodes":1364482},"reviewer-1star-review-rare:Train":{"node_idx_offset":31071048,"num_nodes":2362795},"reviewer-harsh-critic:Train":{"node_idx_offset":36618986,"num_nodes":411270},"reviewer-long-writer:Train":{"node_idx_offset":37441526,"num_nodes":411270},"product-1star-review-rare:Train":{"node_idx_offset":5285494,"num_nodes":1464735},"reviewer-verified-only:Train":{"node_idx_offset":51760421,"num_nodes":411270},"product-premium-review-rare:Train":{"node_idx_offset":17829318,"num_nodes":1464735},"product-multi-1star-rare:Train":{"node_idx_offset":15696091,"num_nodes":1464735},"reviewer-long-review-writer:Train":{"node_idx_offset":37030256,"num_nodes":411270},"cold-start-product-immediate:Train":{"node_idx_offset":3277074,"num_nodes":100152},"product-any-new-review:Train":{"node_idx_offset":7418721,"num_nodes":1464755},"product-total-rating-sum:Train":{"node_idx_offset":24002855,"num_nodes":668492},"reviewer-verified-review-rare:Train":{"node_idx_offset":52582961,"num_nodes":2362795},"product-verified-1star-rare:Train":{"node_idx_offset":25339839,"num_nodes":1464735},"product-mean-rating:Train":{"node_idx_offset":14359107,"num_nodes":668492},"cold-start-reviewer-repeat:Train":{"node_idx_offset":4380898,"num_nodes":301532},"reviewer-mean-rating:Train":{"node_idx_offset":38675336,"num_nodes":411270},"product-max-review-length:Train":{"node_idx_offset":13690615,"num_nodes":668492},"reviewer-total-review-length:Train":{"node_idx_offset":48986356,"num_nodes":411270},"reviewer-rating-trend:Train":{"node_idx_offset":44634736,"num_nodes":213265}}
|
|
|
|
|
|
join-amazon-sports/text.json
DELETED
|
@@ -1,3 +0,0 @@
|
|
| 1 |
-
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:d6f68d9dd8429496fa5c7e29294515192662874dd901c4e3bf8b648d77c2686c
|
| 3 |
-
size 10570830
|
|
|
|
|
|
|
|
|
|
|
|
join-amazon-sports/text_emb_all-MiniLM-L12-v2.bin
DELETED
|
@@ -1,3 +0,0 @@
|
|
| 1 |
-
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:abe296a04d30225e206c452a6513b2cd613e1207568f3b8ddddb544342b4cf5c
|
| 3 |
-
size 271510272
|
|
|
|
|
|
|
|
|
|
|
|
join-amazon0302/column_index.json
DELETED
|
@@ -1 +0,0 @@
|
|
| 1 |
-
{"src of edges":1,"node_id of nodes":5,"identifier of nodes":6,"dst of edges":3,"identifier of edges":4}
|
|
|
|
|
|
join-amazon0302/meta.json
DELETED
|
@@ -1,24 +0,0 @@
|
|
| 1 |
-
{
|
| 2 |
-
"files": {
|
| 3 |
-
"column_index": "column_index.json",
|
| 4 |
-
"nodes": "nodes.rkyv",
|
| 5 |
-
"offsets": "offsets.rkyv",
|
| 6 |
-
"p2f_adj": "p2f_adj.rkyv",
|
| 7 |
-
"table_info": "table_info.json",
|
| 8 |
-
"text": "text.json"
|
| 9 |
-
},
|
| 10 |
-
"format_version": 1,
|
| 11 |
-
"name": "join-amazon0302",
|
| 12 |
-
"num_db_tables": 2,
|
| 13 |
-
"num_nodes": 1496988,
|
| 14 |
-
"num_task_tables": 0,
|
| 15 |
-
"num_text_strings": 7,
|
| 16 |
-
"source": "stanford-star/the-join/join-amazon0302",
|
| 17 |
-
"tasks": [],
|
| 18 |
-
"text_embeddings": {
|
| 19 |
-
"all-MiniLM-L12-v2": {
|
| 20 |
-
"file": "text_emb_all-MiniLM-L12-v2.bin",
|
| 21 |
-
"d_text": 384
|
| 22 |
-
}
|
| 23 |
-
}
|
| 24 |
-
}
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
join-amazon0302/nodes.rkyv
DELETED
|
@@ -1,3 +0,0 @@
|
|
| 1 |
-
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:099f0fc912dd295d2ab3d9f96231a5f22c36a0242e7f659ab82264115142c924
|
| 3 |
-
size 358671696
|
|
|
|
|
|
|
|
|
|
|
|
join-amazon0302/offsets.rkyv
DELETED
|
@@ -1,3 +0,0 @@
|
|
| 1 |
-
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:f87d88a8e329c65c4abb3ecb86668ad5ad7c5db05c9ee4c6ee24b96e975e913b
|
| 3 |
-
size 11975928
|
|
|
|
|
|
|
|
|
|
|
|
join-amazon0302/p2f_adj.rkyv
DELETED
|
@@ -1,3 +0,0 @@
|
|
| 1 |
-
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:d8c6ec492204a749fe20b51105637b8e046b19448f66ee61baef3bb00e2afdc5
|
| 3 |
-
size 73346904
|
|
|
|
|
|
|
|
|
|
|
|
join-amazon0302/table_info.json
DELETED
|
@@ -1 +0,0 @@
|
|
| 1 |
-
{"nodes:Db":{"node_idx_offset":1234877,"num_nodes":262111},"edges:Db":{"node_idx_offset":0,"num_nodes":1234877}}
|
|
|
|
|
|
join-amazon0302/text.json
DELETED
|
@@ -1 +0,0 @@
|
|
| 1 |
-
["edges","src of edges","nodes","dst of edges","identifier of edges","node_id of nodes","identifier of nodes"]
|
|
|
|
|
|
join-amazon0302/text_emb_all-MiniLM-L12-v2.bin
DELETED
|
@@ -1,3 +0,0 @@
|
|
| 1 |
-
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:1fd9b5b49f523d9336eda3823a8623e159da9e3cce04640fddd9af35fc75c82a
|
| 3 |
-
size 5376
|
|
|
|
|
|
|
|
|
|
|
|
join-arnaud-citeseer/column_index.json
DELETED
|
@@ -1 +0,0 @@
|
|
| 1 |
-
{"paper_id of content":3331,"word_cited_id of content":3333,"class_label of content":7037,"paper_id of paper":7045,"identifier of content":7044,"cited_paper_id of cites":1,"citing_paper_id of cites":1964,"class_label of paper":7046,"identifier of paper":7047}
|
|
|
|
|
|
join-arnaud-citeseer/meta.json
DELETED
|
@@ -1,24 +0,0 @@
|
|
| 1 |
-
{
|
| 2 |
-
"files": {
|
| 3 |
-
"column_index": "column_index.json",
|
| 4 |
-
"nodes": "nodes.rkyv",
|
| 5 |
-
"offsets": "offsets.rkyv",
|
| 6 |
-
"p2f_adj": "p2f_adj.rkyv",
|
| 7 |
-
"table_info": "table_info.json",
|
| 8 |
-
"text": "text.json"
|
| 9 |
-
},
|
| 10 |
-
"format_version": 1,
|
| 11 |
-
"name": "join-arnaud-citeseer",
|
| 12 |
-
"num_db_tables": 3,
|
| 13 |
-
"num_nodes": 113209,
|
| 14 |
-
"num_task_tables": 0,
|
| 15 |
-
"num_text_strings": 7048,
|
| 16 |
-
"source": "stanford-star/the-join/join-arnaud-citeseer",
|
| 17 |
-
"tasks": [],
|
| 18 |
-
"text_embeddings": {
|
| 19 |
-
"all-MiniLM-L12-v2": {
|
| 20 |
-
"file": "text_emb_all-MiniLM-L12-v2.bin",
|
| 21 |
-
"d_text": 384
|
| 22 |
-
}
|
| 23 |
-
}
|
| 24 |
-
}
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
join-arnaud-citeseer/nodes.rkyv
DELETED
|
@@ -1,3 +0,0 @@
|
|
| 1 |
-
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:470fd402a1c12e8e3226157fcb56fbb70126732f40a4d5f2f799b43304ec018a
|
| 3 |
-
size 30406736
|
|
|
|
|
|
|
|
|
|
|
|
join-arnaud-citeseer/offsets.rkyv
DELETED
|
@@ -1,3 +0,0 @@
|
|
| 1 |
-
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:e9699b0d12f447a246133abba56126d57c0e79b54d0280d7cebbbd7c2f9cf497
|
| 3 |
-
size 905696
|
|
|
|
|
|
|
|
|
|
|
|
join-arnaud-citeseer/p2f_adj.rkyv
DELETED
|
@@ -1,3 +0,0 @@
|
|
| 1 |
-
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:7ff501a5145f6ca548dc1ec74cfa5404dd5ed6f8bca08aeea857d0c70bffefc1
|
| 3 |
-
size 3914664
|
|
|
|
|
|
|
|
|
|
|
|
join-arnaud-citeseer/table_info.json
DELETED
|
@@ -1 +0,0 @@
|
|
| 1 |
-
{"content:Db":{"node_idx_offset":4732,"num_nodes":105165},"paper:Db":{"node_idx_offset":109897,"num_nodes":3312},"cites:Db":{"node_idx_offset":0,"num_nodes":4732}}
|
|
|
|
|
|
join-arnaud-citeseer/text.json
DELETED
|
@@ -1 +0,0 @@
|
|
| 1 |
-
["cites","cited_paper_id of cites","100157","100598","101570","10227","103027","105684","106003","106339","108321","108573","108580","110962","11099","111340","111958","112493","11264","114091","11423","114563","114630","11510","115410","115971","116087","116696","116882","11708","119174","119409","120432","12369","124100","124833","125291","125615","126894","130387","131492","131669","13229","132458","132577","133494","13423","137638","138121","13839","138451","140079","142848","14331","146066","14648","14656","147375","147521","147739","149759","150449","150514","15156","1529","15340","154973","156949","157013","157253","161260","1625","162997","1639","164846","164953","16755","16892","169000","171304","172324","172950","180347","18124","184462","184682","187087","187693","18832","18855","18915","1894","19017","190915","191426","19199","192612","192987","19461","19462","194986","196686","197022","197556","198191","198731","199764","200188","20100","201746","201850","201909","202521","202938","203721","20379","20543","2056","20587","206655","20706","210","2102","210603","21158","212779","21283","212834","214340","21655","220216","22140","22187","22358","226124","226296","226643","22778","22863","22903","230265","23217","232670","233063","233508","235064","235466","236095","236597","23799","240151","241799","242172","242836","24318","243680","24402","244548","245254","24549","246390","249151","250204","250432","250815","25225","253088","25329","254041","254597","254693","257148","25809","261862","263737","263968","26484","267501","267965","270207","270469","271585","274436","27645","276915","277650","280639","28223","282608","28307","28315","284454","285081","286829","288424","289676","28981","292223","292524","29319","293286","294039","294238","295186","295196","29551","295535","296568","298782","298827","298894","299008","300048","300232","300852","301428","301461","30237","302575","306529","307133","307268","308936","308951","310158","310437","311175","31199","31326","314295","314651","315017","315336","317766","319242","322562","323158","323163","323867","323955","32409","324100","32521","32742","328087","328242","32986","329890","329899","330661","33084","332050","332626","332789","335912","340342","340473","340855","34322","34341","345377","346149","352769","352789","353348","35592","356540","35804","35997","3602","362156","363813","364207","364516","367226","367649","369039","3733","373966","373986","374208","375253","375424","376961","37804","38137","382181","382561","38408","386535","386938","387202","389181","38927","390217","397163","399288","40032","400733","402224","402592","40513","405764","408262","408356","412941","412974","414073","414088","41721","41784","419282","421686","422169","423028","4251","425424","428001","42875","43223","43410","43488","43511","4363","43702","440022","440714","440927","441053","441654","442160","442980","448486","448769","448928","449669","449833","450055","450284","45086","451065","452225","453602","453999","454077","454876","455220","455336","45542","455426","455511","455679","455997","457130","4579","4588","459286","45960","460350","460784","461688","462179","46363","4664","467872","46840","46858","470345","470572","471147","471293","475183","47625","476368","4799","48055","48156","482081","487862","488749","491166","492133","494575","49524","50068","501178","50141","50203","50337","505452","506507","508147","509926","51036","51542","51607","518472","5188","520593","52576","527475","529503","53191","532140","538013","539761","54866","5541","55643","55740","55934","56093","56124","56231","57205","5749","60236","60365","60728","60765","61706","62580","62931","63224","63694","6411","64225","6439","64654","64765","65714","65816","66208","6729","67522","67963","68306","6875","68836","70265","7036","71059","71076","73094","74239","7436","74980","7537","75402","76283","77796","7785","78138","78173","78547","7980","81142","8204","82362","8263","83259","83444","845","84830","85838","87014","87928","88449","89078","8922","89384","8956","90208","90507","90601","9105","91978","92649","940","94069","94992","9546","9576","95786","95810","95871","9619","96518","9683","98111","abberley99thisl","abello99maximum","aberg01collection","abiteboul01representing","abiteboul98logical","abowd00charting","abowd00classroom","abraham00optimal","accot97beyond","acharya98active","acharya99selectivity","adams99stable","advani99integrating","aggarwal01intelligent","agichtein01learning","agouris98intelligent","agrawal00athena","aguil00querying","aha91casebased","aha97casebased","aha97learning","aha98feature","aha98omnipresence","ahamad99scalable","aksoy98textural","alferes98dynamic","ali00incremental","allen01towards","allen99control","almeida01analyzing","amato98obprm","amato98supporting","ambite00flexible","ambite01simplifying","ambite98ariadne","ambroszkiewicz97model","ambroszkiewicz98cooperation","ambroszkiewicz98team","amin01agentbased","amin99agentoriented","amiri00dynamic","amiri00highly","amitay98using","amyot00extension","anastasi99reliable","andersen00what","andersson99intelligent","ando03mostlyunsupervised","andre98integrating","andre99integrating","antoniou98normal","aoki99realtime","appiani00multiagent","arai01multiagent","arampatzis00evaluation","argamon98routing","arge99efficient","arisha99impact","arkin98cooperative","arleo00spatial","armstrong99boticelli","aron99efficient","artale01reasoning","artale01temporal","asada00overview","asada98robocup","ashish98optimizing","ashri00paradigma","aslam98static","athnes00human","attardi99theseus","aylett00applying","azuma99challenge","azuma99tracking","baader98matching","bachpedersen98multidimensional","baerentzen97learning","bagnell01autonomous","bailey01analysis","bailey95active","baker01heuristic","baker98distributional","baker98survey","balch94communication","balke00applications","bandi98space","banko99generating","baral00reasoning","baralis00algebraic","barbosa01tox","bardram97plans","baron99voxelbased","barros96business","barros97towards","bartoli01three","barve99modeling","basili00language","basin99reflective","bassiliades00edevice","bastert01landscapes","basu01evaluating","bates98state","bates98using","bauer99infobeans","bauer99trias","baulier00datablitz","baumgartner01supervised","baxter01dab","beaudouin-lafon00instrumental","bechhofer01oiled","becker99gripsee","bederson00jazz","bederson95pad","beeferman99statistical","beetz98causal","beigi97metaseek","beigl00mediacups","benerecetti97model","benetti01sidesigner","beneventano00information","benford00designing","benitez98contentbased","benitez98using","bennett00combinations","benoit98audiovisual","benton98compiling","benzaken98static","bergamaschi98intelligent","bergamaschi99intelligent","bergamaschi99semantic","bergmark02collection","bernstein00data","bernstein00panel","bernstein00vision","bertelsen99dynamics","bertino01measuring","bertino98definition","bertino99approach","bertino99enhancing","bettini01klava","bettini99symbolic","beuster00mia","bhalotia02keyword","bharat98improved","bharat99comparison","bihlmeyer98dlv","billard98experiments","billinghurst98wearable","billsus00learning","binder01design","bishop98gtm","biskup00constraints","biskup00decomposition","bjrk00powerview","black98probabilistic","blockeel00executing","blockeel98topdown","blum01learning","bohlen00temporal","boley99document","boll99emp","bollacker98citeseer","bollacker99system","boloni99multiplane","bolotov99clausal","bomze99maximum","boncz98flattening","bongard00legion","bonifati01pushing","bonifati01warehousing","bonner98logic","bonnet98partial","bonnet99query","borchers00pattern","boros98how","borrajo93bounded","botchers96layout","bowling01convergence","bowling01rational","bowman99interaction","bradford98performance","bradford98pruning","bradshaw97introduction","brafman98knowledge","brand00style","brandt00antisocial","brandt00exploring","brandt00task","brandt01cryptographic","brandt01vicious","brass98semantics","brass99computation","brass99equivalence","braumandl98evaluating","brazier01automated","brazier02agent","brazier99compositional","breazeal98regulating","bredin99economic","brewington99mobile","brin98anatomy","brin98what","broekstra02enabling","brown01switch","brown98iadea","brown98utility","brown99active","bruckner01managing","bruderlin97hierarchical","brumitt00better","bruni00algebraic","bruno01stholes","bruno02evaluating","brusilovsky98adaptive","bruyninckx00autonomous","bryson00architectures","bryson00crossparadigm","bryson00making","bryson00study","bryson01modularity","buckinghamshum00scholonto","bui99invariant","buneman98path","burke01salticus","burkhard99bdi","burnett00exception","busetta99jack","busi00expressiveness","butz00augmenting","butz01algorithmic","buyukkokten00seeing","buyukkokten99exploiting","cabri00mars","cabri00xml","cabri01engineering","cabri98reactive","cacheda01superimposing","cachin99computationally","cadoli98survey","cal01accessing","cal02expressive","callan99automatic","calvanese00containment","calvanese01description","calvanese99unifying","camacho00multiagent","camacho00travelplan","camerer00ewa","cantu-paz00using","caragea01analysis","carbonell98report","cardie93using","cardie97improving","cardie99guest","carr01conceptual","carreras01hybrid","carro99concurrency","carson99blobworld","carvalho00hybrid","carver00methodology","casati01improving","casillas00improving","casillas00methodology","cassell00more","cassell00nudge","cassell01more","cassell02mack","cassell99fully","cassell99requirements","castelfranchi99deliberate","ceska01generating","cetintemel00selfadaptive","chagas98learning","chakrabarti01integrating","chakrabarti02accelerated","chakrabarti98automatic","chalmers98order","chamberlin00quilt","chan98approximate","chan98toward","chan99possible","chang98data","chang98global","chang99approximate","chang99automatic","chaudhri98okbc","chen00algebraic","chen00features","chen00niagaracq","chen00websail","chen01txnwrap","chen98webmate","chen99dna","chen99dynamic","chen99introducing","cheverst00developing","chien00comparative","chien00version","chien01efficient","chirkova00linearly","cho00synchronizing","choppy00control","christel98information","christel99interactive","christiansen99integrity","christina99detecting","chung01dynamic","ciaccia00imprecision","cicirello01wasp","ciravegna00bringing","ciravegna00learning","clark00finding","clark00location","clark00what","clarkson00recognizing","claypool99combining","claypool99ounce","cleary00generating","cluet99using","codish98efficient","coellocoello99treating","coetzee00feature","cohen98integration","cohen98joins","cohn01missing","cohn01qualitative","combs99does","conati00toward","conrad00xml","coppin00eventscope","cox96introspective","crabbe01goal","crabbe99secondorder","craswell00server","craven98learning","cremonini00ruling","crescenzi01roadrunner","critchlow98automatic","critchlow98metadata","cruz99preserving","cruz99user","cui01lineage","cui99practical","cumby00relational","cummins99automatic","cunningham99experience","czajkowski98jres","dahl99eel","damiani97semantic","damiani97structuring","dantsin99complexity","das98rule","datta98case","davison00topical","davison99discoweb","dayal01business","dean99finding","decarolis00verbal","decker01multiagent","decker95coordination","decker95environment","decleir99database","defalco98optimizing","degaris99building","degeratu01latencydependent","dekhtyar99probabilistic","delgado99multiagent","della99internet","deloach01analysis","deloach01specifying","deloach99multiagent","denoue00annotation","denti00luce","denti99from","deutschmann98compressive","devanbu99chime","devaney98needles","dewhurst98knowledge","dhillon01coclustering","dhillon01concept","diaconescu99componentbased","diao00comparative","diao00toward","dicaro98antnet","dick99mocsyn","dietterich98approximate","dignum00towards","dimitrova02web","dinverno97formal","dipasquo98using","dix01metaagent","dix98nonmonotonic","dix99places","dolan00benchmarking","dom99mining","domingos00mining","dong99maintaining","donini98allog","dorohonceanu00novel","dotsch00tic","dotsch96good","dourish01seeking","dragoni00updating","dreilinger96information","dreilinger97experiences","driessens01speeding","drori00using","druin01designing","druin99designing","druin99role","du97categorization","dubois99classification","duch00computational","duch00optimization","duch98minimal","dumais00hierarchical","dumas98handling","dunlop00development","dutech01multiagent","dwork01rank","dwyer99patterns","dyreson99capturing","dyreson99efficiently","dzeroski98detecting","edmond98achieving","efe00shape","ehmann01accurate","eidenbenz00atomi","eijk98informationpassing","eiter00extension","eiter98firstorder","emmerich00implementing","erdem98task","eriksson98sics","escudero00boosting","escudero00portability","esposito00machine","essa99computer","ester00dctree","ezeife01selecting","faber98representing","faensen01hermes","falk99amplifying","falk99bubblebadge","fang98computing","faruquie00translingual","fauvet99applying","fayyad98initialization","feder00computing","fegaras98new","fegaras98query","fegaras99voodoo","feiner99wearing","fels98glovetalkii","fensel00workshop","fensel98ontobroker","fent00logical","ferguson95role","ferhatosmanoglu01approximate","feris00detection","fernandes00combining","fernyhough99constructing","ferragina98string","fertig99fuzzy","fickas99when","fiebig97raw","fikes99distributed","filho98gathering","fink99adaptable","finn01fact","finn02genre","fischer00user","fischer96intelligent","fjeld98build","flach00abduction","flach98strongly","flach99database","flake00agents","flake00efficient","flank98layered","fleuret99graded","florescu00integrating","florescu99performance","florescu99query","forlizzi99data","fox98active","fox98position","fox99gateway","fox99sentinel","franconi00icom","frank98generating","freitag99information","french98evaluating","french99effective","freund98self","friedman99learning","fuhr98hyspirit","funt98is","gabbard98usability","gaizauskas98information","galhardas00extensible","ganti98clustering","gaskett00reinforcement","gellersen00adding","georgeff99beliefdesireintention","ghani00data","ghani00using","ghani01using","giampapa00agent","gibbins01scalability","ginsberg99gib","ginsburg98annotate","girod00development","globig94casebased","glover00web","glover01improving","glover02using","glover99architecture","glover99recommending","goasdoue00rewriting","godfrey97minimization","godfrey98integrity","goecks99automatically","goguen99social","goldberg00eigentaste","goldberg99coordinating","goldberg99optimizing","goldman00enhancing","goldman98interactive","goldstein99automatic","good99combining","goodman01representation","gotoh00topicbased","gouveia98technological","graef00construction","graham00towards","grandi00generalized","granger02multiscale","granlund01patternsupported","gratch00emile","gray01dagents","greenberg98using","greenberg99adapting","greenwald01autonomous","greiff98theory","grieser00unifying","griffiths95concept","griffiths99cooperative","grignon99multiobjective","grimm01systems","groh99automated","grolimund95integrating","grundy01developing","guessoum99from","gunn98support","guo00learning","gustafson00adapt","ha98geometric","haarslev99description","haddaway99overview","hahn95integrating","halevy00theory","han99automated","han99efficient","handschuh02authoring","hannebauer99rapid","hanson99scalable","harel99workload","harik99linkage","harik99parameterless","haritsa00realtime","hart99comparing","hattori99socialware","hatzilygeroudis00neurules","hatzilygeroudis01hymes","hawking01measuring","hayashi00comparison","hayden99architectural","haynes96learning","hayzelden99agent","hazelhurst98binary","heidemann01building","heinonen96www","heinze99plan","heinzmann98visual","hekanaho98dogma","hellerstein00recognizing","hellerstein98optimization","helmer01automated","helmer01software","helvik01using","herbrich99regression","herlea01secure","herlocker00explaining","hermansky98traps","hermsdorf98webadapter","hero98robust","heskes98solving","hespanha99multipleagent","hetzler98multifaceted","heydon01vesta","himberg01time","hinze01how","hirai99webbase","hoadley99between","hodkinson99decidable","hofmann99probabilistic","hohl99nexus","holden97visual","hollerer99exploring","hollerer99situated","holliday00database","holliday00exploiting","holmquist00play","holmquist99supporting","holtman98automatic","honavar98distributed","hoppenbrouwers98browsing","horling01using","horling99diagnosis","horling99using","horrocks98using","horvitz99principles","hoste00rule","hourcade99architecture","howe97examining","howe97savvysearch","hu00mobile","hu01overview","huang00dialogue","huang00running","huang01architecture","huang01programmability","huffman94instructable","huget02agent","huget02application","huget02extending","huget02language","huget02model","hunter98ramification","huntsberger98bismarc","hupfeld00spatially","hussain98attribute","hustadt00normal","iglesias99survey","ijspeert98evolving","ijspeert99evolution","inoue99computing","ishida99digital","itti98model","iyer00boosting","jacob99software","jagadish99querying","jain99statistical","jakobi98minimal","jakobi98running","jamil00gql","jamil01case","jamil99belief","jansen00mobile","jantke93casebased","jantke93types","jantke94nonstandard","jantke97logical","jantke97necessity","jantke97theoretical","japan98learning","jarke00concept","jarke99architecture","jeh02scaling","jeh02simrank","jennings00autonomous","jennings95controlling","jensen99learning","joachims00estimating","joachims02unbiased","joachims99transductive","johns01how","johnson99cambridge","jonker99multiagent","jordan98introduction","jording97anthropomorphic","joslyn99levels","jourlin99general","jr99identifying","junker98learning","jurisica96inductive","kaburlasos00learning","kagal01highly","kaljuvee01efficient","kang00visualization","kantarcioglu02privacypreserving","karadkar00evolution","karkanis00image","karlgren98iterative","karlgren98stylistic","karnik99security","karypis00concept","kasif98probabilistic","kaski98dimensionality","kaur98improving","kayan99evaluation","kemme00new","kemme98suite","kendall00java","kendall97application","khaled98gado","khardon99relational","khudanpur99maximum","killijian01towards","kim00using","kim01secret","kim99compensatory","kim99effective","kinny96methodology","kinny97modelling","kirste01reference","kitano97robocup","kitano99robocup","klein91supporting","klein99computer","kleinberg98microeconomic","klinkenberg00detecting","knight00system","knight00virtual","knoblock00accurately","knowles99evolutionary","knowles99pareto","knublauch00towards","kobayashi00information","kobayashi99information","koch00integrating","koch99simple","kodratoff00comparing","kohrs99improving","kohrs99using","koller98probabilistic","kollios99nearest","kon00flexible","kon00secure","kon00using","konda01actorcritic","kononenko95induction","koperski98mining","kopp00knowledgebased","kopp00planning","kortuem99close","kosala00web","koster99normalization","kostiadis99multithreaded","kotz99mobile","koubarakis99querying","koubarakis99tractable","kowalski98executing","kowalski98from","krink00parameter","kruschwitz00extracting","kubiatowicz00oceanstore","kueng01holistic","kumar00adaptive","kumar01behaviorbased","kumar98beyond","kurki99agents","kushilevitz98efficient","kushmerick00wrapper","kusiak00decomposition","kutulakos96affine","kwedlo99evolutionary","kwok01scaling","kwok98automated","laaksonen99picsom","labrou99agent","lacorte99agent","lagoze01open","laird94evolution","lam99broadcast","lam99feature","lamma99strategies","landau01atnosferes","langheinrich00first","langley94oblivious","langley95applications","larocque00reversible","larsen01probabilistic","lau00version","lau99privacy","lau99programming","lavalle99randomized","lavalle99visibilitybased","laviola99flex","laviola99msvt","laviola99wholehand","lavrac00intelligent","lawrence00context","lawrence98context","lawrence98searching","lawrence99searching","lawrence99text","layzell98new","lee00spectral","lee00training","lee01collaborative","lee99unifying","lenzmann97contractnetbased","lerner99comparative","lesh99using","lester97cosmo","leung98probabilistic","leuschel98creating","levene00computing","levene01web","levene99justification","levene99probabilistic","levison96connecting","li00automatic","li01indexing","li98adome","li98automatic","liebig99event","liechti99nonobtrusive","lien98automated","likas99training","lim00comparison","lim98extracting","lin01efficiently","lin02acird","lind01issues","liskov99providing","litman99empirically","littman99solving","liu00design","liu00extended","liu00implementation","liu98face","liu98relationlog","liu98statistical","liu99deductive","liu99face","liu99overview","livingston01closing","ljungstrand99wearboy","ljungstrand99webwho","llc00deep","lobo99extended","locatelli00simulated","logan00distributed","lohse97consumer","lomuscio00classification","lovell98feature","loyer99computing","luck01conceptual","lueg98supporting","lukasiewicz00probabilistic","lyons00guided","macintyre96future","mackay98augmented","macskassy01intelligent","madhavan01generic","mair99investigation","makar01hierarchical","malis98positioning","mamoulis98integration","mankoff00providing","mankoff98bringing","manmatha01modeling","mann01partial","mann01validating","mannila99prediction","marchionini98interfaces","marchiori98simple","marini00hemasl","marini00specification","mark00multiagent","markatos98effective","markatos99caching","marmasse00locationaware","marmasse99commotion","marques00going","marques01integrating","marques01providing","marsella98instructors","marsella99being","marsh00maintaining","marsh00using","marsh99cooperative","marsic01adaptive","martelli99logic","martelli99specification","martin00knowledge","martin99embedding","mascardi99agentbased","mascolo99finegrained","massink99towards","mataric00sensorymotor","mataric99making","matthews99fuzzy","matzinger98computational","maurer00second","maynard01named","mazumdar99achieving","mcbreen00experimental","mccallum00maximum","mcdonald00heterogeneous","mcgovern01automatic","mchugh98indexing","mchugh99optimizing","mcilraith01semantic","mcroy95repair","medl98multimodal","meeden98trend","menczer01evaluating","menczer99adaptive","meng99database","meng99estimating","menzies00issues","meretakis00scalable","merro01bisimulation","mertz98conception","merz99genetic","meuss98dag","meyer99automatic","michaelides98uniform","michail99assessing","michaud98learning","michaud99managing","michaud99representation","middleton01capturing","mihalcea98word","miles00designing","miller00training","miller99genetic","milo00typechecking","minar99cooperating","minar99hive","mirmehdi01extracting","mistry01materialized","mitra01data","mittal99selecting","mizoguchi00using","mladenic98turning","moghaddam98beyond","mohan99repeating","moizumi98mobile","molz00design","moon00scalable","moon98scalable","mooney00contentbased","moran99improvement","more00tertiary","moreno95alisis","moreno96limited","moreno97dynamic","moreno97how","morse00collablogger","moukas96amalthaea","mudgal00bilateral","muhlenbein99convergence","muller00eventdriven","munetomo99identifying","munro99footprints","munroe00bbq","munzner95visualizing","murphy01lime","murray01specifying","murray98kaleidoquery","murthy99context","muscettola98reformulating","muslea00selective","muslea01hierarchical","muslea99hierarchical","muth99integrating","myers96easily","myers97amulet","myers98brief","nagi99implementation","nahm00mutually","nahm00using","nahm01mining","najork01breadthfirst","najork01highperformance","narayanan99reasoning","nascimento99evaluation","naumann00assessment","naumann00completeness","navarro00adding","neaves98dynamic","nehaniv99meaning","neti00perceptual","neumann99augmented","neumann99constructing","neumann99experience","ng98reconfiguring","nguyen01monitoring","nguyen98strict","nichols01using","nicola99increasing","nie01joint","nie01mining","nigam00analyzing","nigam99text","nijholt00multimodal","nissen99repository","noda99discovering","nodine98overview","noh99uncertain","norman95goal","norman97motivationbased","norrie00extended","nottelmann01learning","nrvag98analytical","nrvag98optimizing","nwana99perspective","oakley00putting","oard01evaluating","obst01specifying","ockerman98preliminary","oh00efficient","oliboni01temporal","oliveira00agents","oliver98graphical","oliver98statistical","oliver99bayesian","olson98probabilistic","onoda98asymptotic","opper99mean","ordonez00discovering","ordonez99discovering","oria99defining","orovas00cellular","orovas98cellular","orr00smart","overeinder02multiagent","oviatt99ten","ozden98cyclic","padgett98simple","page98pagerank","pagonis99evolving","pal01rough","panayiotopoulos98intelligent","pant02exploration","pant02myspiders","panzarasa01organisation","panzarasa99modeling","papadias01efficient","papadias01indexing","papadopoulos00models","papakonstantinou98query","papazoglou99contextualizing","paradis98virtual","paradiso00design","paradiso99cybershoe","paradiso99interactive","parekh00constructive","paris00common","park01segmentbased","park98alternative","park99costbased","parker98adaptive","parsons98agents","parsons99approach","parunak01erims","pascoe98adding","paton99active","paulson00inductive","pavlovic97visual","pazzani00representation","pedersen99supporting","pelikan99bivariate","pelikan99boa","pentland99digital","pfoser00novel","phan01new","phan01scalable","piater99toward","picard98humancomputer","picault00robots","picco99lime","piekarski99architecture","pinheirodasilva00generating","pinheirodasilva00user","pirjanian00multirobot","pitoura01locating","pitoura99exploiting","pitoura99scalable","plaisant99design","poggi00eye","pohl99machine","polani99fast","ponnekanti01icrafter","popescul01probabilistic","poupyrev98virtual","pouwelse99feasible","powell00impact","prasad96cooperative","prasad96distributed","prasad99learning","precup01offpolicy","prokopenko98designing","prokopenko99situated","przymusinski98autoepistemic","puliafito00map","punyakanok01use","puzicha99theory","quek95eyes","queloz99foreign","racine97maintaining","raghavan01crawling","raisamo99evaluating","ram90incremental","ramampiaro00supporting","randell00shopping","rao94meansend","rao95bdi","rao95formal","rao96agentspeakl","rao97unified","rasheed97guided","rauber01automatically","rauber01integrating","rauterberg97gesture","rauterberg98build","rehg99visionbased","renambot00cavestudy","rennie01improving","resnik98parallel","resnik99mining","rey01location","rhodes99wearable","ricci01enlightened","ricci97extending","rickel98animated","rickel98taskoriented","riedel98active","riely99trust","rintanen98planning","rizzo97personalitydriven","rocha99syntactic","roddick99towards","rom00gaia","roman00legorb","rosenstein99continuous","rosenthal00view","ross98complex","roth00snowbased","roth00using","roth01programming","roth98learning","roubos00compact","roubos00learning","rousseau96personality","rousseau97socialpsychological","rousskov98cache","rowley98rotation","roy00integration","roy01toward","roy99coastal","rui00optimizing","rui99image","rundensteiner98capacityaugmenting","rungsarityotin00finding","sabater99engineering","sadri00abduction","sadri99abduction","sadri99computational","sahin98visual","sakakibara94learning","sakama99updating","salles98development","sampaio98deductive","samtani98recent","sandholm01algorithm","sandholm01cabob","sandholm01market","sandholm01side","sandholm01winner","sandholm99algorithms","santini99similarity","santos97introductory","santos99dynamic","sarawagi00data","sarawagi98discoverydriven","sarkar01applying","sarwar01itembased","sato01parameter","satoh01flying","satoh01network","sattler01data","sawhney99nomadic","scassellati98building","schadler97connectionist","schadler98application","schaedler97connectionist","schaller99reclustering","schapire98boosting","schattenberg00planning","sche01active","scheffer01active","schein01generative","scheuermann98data","schiele99attentional","schmalstieg00bridging","schmalstieg99using","schmidt00implicit","schmidt01how","schmidt01xml","schmidt99advanced","schmill99learned","schmitt98relating","schnattinger98qualitybased","schndelbach01augurscope","schneider00disseminating","schneider99distributed","schohn00less","schuldt99concurrency","schuldt99transactional","schut00intention","schut01principles","schwab00learning","schwabacher96use","schwabacher98multilevel","schweighofer01automatic","schweiss99architecture","scime01websifter","sen98individual","sengupta99constructing","seo00reinforcement","setiono99mapping","seymore99learning","shah99amdb","shan98introduction","shankar00weight","shanmugasundaram99efficient","shapiro98embodied","shavlik98building","shavlik99instructable","shaw98clause","shehory99emergent","shehory99feasible","sheng99graph","shintani98parallel","shneiderman00direct","shneiderman99creating","shneiderman99supporting","shu98using","siddiqi98shock","silverman01more","sim99learning","simula99selforganizing","singhal99document","singletary01symbiotic","sistla98querying","skarmeas99component","sloman02how","sloman98architectures","sloman99building","slonim00document","slonim01power","sma98theory","smeaton97relevance","smith00conversation","smith01management","smola98from","smola98general","smyth99surfing","soderland99learning","spoelder00man","squire99improving","sreerupa98dynamic","stader98intelligent","stanoi00reverse","stanoi98weak","starner00gesture","starner98realtime","starner98visual","stepaniuk98optimizations","sterritt00exploring","sterritt01soft","stewart99single","stolzenburg00spatial","stone01architecture","stone98layered","stonebraker01content","streitz01roomware","streitz98roomware","streitz99iland","sturm00tableau","subramanian98costbased","sudo01automatic","sukhatme99embedding","sullivan98tribeca","sullivan99model","sun98some","sun99from","sun99optional","surmann01learning","suryadi99learning","sutton93online","szabo95virtual","szummer01kernel","szymkowiak01hierarchical","tabuada01feasible","takahashi00location","takahashi98mobile","talim01controlling","tan01predictive","tarau99jinni","tenhagen01continuous","terrillon98automatic","terveen98evaluating","terveen99constructing","theilmann99disseminating","thevenin99adaptation","thomas98wearable","thomason00desires","thompson99active","thrun98framework","thrun98map","tice00key","tice00practical","tieu00boosting","timm00multiagent","timm01synthesis","tino98finite","tobies99pspace","toenshoff01flexible","tong00restricted","torp99effective","tourapis01advanced","traum96reactivedeliberative","tresp98description","tripathi99mobile","turk00perceptual","turner00improving","turney00learning","turney99learning","tzitzikas01democratic","tzouramanis00multiversion","tzouramanis00overlapping","tzouramanis99overlapping","uhrmacher00modeling","uhrmacher00plug","urhan01dynamic","urhan98costbased","vagina03cryptographic","vaidya02privacy","valencia98algebraic","vandertorre00contrarytoduty","vandertorre98diagnosis","vandertorre99violation","vaneijk01generalised","vanhoof98specialising","vanlaerhoven00teaching","vanlaerhoven00what","vanlaerhoven01combining","vanlaerhoven01realtime","vanschooten00process","vanschooten01structuring","vanthong00speechbot","vanzwol99searching","varela99ant","vasconcelos99probabilistic","veloso98playing","vianu01web","vilalta00quantification","vitek99secure","vitter99external","vogler99toward","vogt99fusion","voncollani99neurofuzzy","waern98concall","wagner97artificial","wah00constrained","wan01realtime","wang00concept","wang00nonmonotonic","wang00using","wang01agentoriented","wang01supporting","wang98quasistable","wang98structure","wang99critical","wang99discovering","wang99hierarchical","ware00reaching","ware96evaluating","warshaw98monitoring","warshaw99rulebased","watson99embodied","weber00unsupervised","weber01textual","weinstein99agentbased","weiss98answer","weiss98intelligent","weiss98learning","wendler98cbr","weng95shoslifn","weng98visionguided","werger00ayllu","wersing00competitive","wess94casebased","wetzel98semantic","white98towards","whittaker00jotmail","wicke99compiling","widom00wsqdsq","wiederhold95valueadded","wiederhold96conceptual","wiesmann99systematic","wijsen99temporal","wilensky00digital","wilhelm99introducing","williamson00approximating","wills00open","wilson01framework","wisneski98ambient","witten00building","witten01power","witten99greenstone","wolf00expert","wolpert99general","wolski98fuzzy","wolter00spatiotemporal","wonsever01contextual","wood00overview","wooldridge00agentoriented","wooldridge00computationally","wooldridge02model","wooldridge98intention","wooldridge98tableaubased","wooldridge99methodology","wroblewski00analyzing","wu00adaptive","wu00discriminantem","wu01capturing","wu01towards","wu99firstorder","xia99comprehensive","xu00maintaining","xu01framework","xu98neural","yagiura99variable","yang00improving","yang00shopping","yang00temporal","yang98extraction","yang98feature","yang99mixtures","yangarber01scenario","yao98making","yen01cast","yim00architecturecentric","yin00knowledgebased","younes00calibrating","yu01progressive","yu99efficient","yu99finding","yu99methodology","yvon94selflearning","zaiane98discovering","zambonelli01organisational","zamir98web","zamir99grouper","zelikovitz00improving","zhang01dyda","zhang01maximum","zhang01pvm","zhang01supporting","zhang99evolving","zhang99sdcc","zhang99situated","zhao98empirical","zheng98stochastic","zhu00incorporating","zhu00segmenting","citing_paper_id of cites","38848","bylund99coordinating","gray99finding","labrou01standardizing","nodine99active","455651","marquez00machine","krasnogor00memetic","sima00computational","sima01computational","140169","weiss00building","104129","amer-yahia00boundingschemas","arlein99making","shasha02algorithmics","73962","83140","bailey02eventconditionaction","tova99active","cohen01learning","raman01potters","wichert00compositionality","itskevitch01automatic","405310","apte01ai","roumeliotis99circumventing","chu-carroll99conflict","23381","heintz00robosoc","veloso99cmunited","ostrovsky01polynomial","zaragoza99dynamic","chantemargue99collective","313926","cai01geovibe","sanchez98agora","257648","453663","57340","452192","bowman01introduction","mundell99towards","ventura99isocrob","540501","gajos01design","peters02using","wijngaards01mas","vanschooten99report","goller99connectionist","goller99feature","brabrand99ltbigwiggt","bouguettaya99using","516803","griffiths01query","159727","wijsen99generalizing","83728","moerland00line","agarwal01time","chomicki99animating","grumbach00manipulating","415056","slivinskas00foundation","518092","nigam01using","kullbach99querying","manolescu01efficient","zadorozhny01validating","konrad98model","konrad99model","461740","bauer99where","reitmayr01mobile","reitmayr01wearable","486074","506324","294031","baldan01mutaclp","coelho00developing","122529","cabrera01proactive","ding01probabilistic","joachims01statistical","ng01stable","277897","roobaert00comparison","roobaert00directsvm","roobaert99viewbased","535300","342407","33385","469106","534720","rodriguez00learning","451495","226856","ian99kea","284772","290879","staab00from","kruschwitz01exploiting","412057","bahle02efficient","clarke01exploiting","hawking01which","singhal01case","449529","abecker01decor","christophides00community","rabarijaona99building","441191","wache01ontologybased","ramakrishna00similarity","442965","bassiliades01interbasekb","liu00threedimensional","bergo01text","kuo00web","goldstein00creating","broersen00leveled","453469","374383","348038","zaki00sequence","454640","bohte00current","529793","iksal01revisiting","vdovjak01rdf","stolzenburg01from","dautenhahn99studying","scassellati99knowing","may99how","279508","376145","ipeirotis01probe","128773","martinez99face","patterson02context","rosario99synthetic","449621","475405","ghani01combining","boyapati00towards","343493","382379","dumas99sequencebased","kushmerick02adaptive","kushmerick02finitestate","452506","ghavamzadeh01continuoustime","jonsson01automated","cvetkovic99genetic","382301","384644","ravat99towards","pan00prosody","386167","quan00argos","476601","bieman01finding","drori01algorithm","popescul02towards","32197","4495","538938","yang01pms","bonner98state","340534","deweerdt00plan","erwig00querybytrace","murthy00concept","459233","478775","526689","alvarez00web","sim00to","ferhatosmanoglu01constrained","524282","greenberg01phidgets","zunino01representing","453948","474167","bush01styx","david01agentbased","boyle00grouplab","443403","doan99efficiently","ives00adaptive","kreuziger92application","28031","baker00hallucinating","martinez00recognition","weng00incremental","weng99face","zhao00sfs","roddick00beyond","zhou00implementation","inoue01controlling","ulrich00appearancebased","marsella00interactive","kanungo99omnipage","536962","faber99using","297471","538839","471747","496736","feng01towards","395537","arge02optimal","459109","liu01drawcad","liu99olog","liu99rol","196348","147445","509763","nguyen00active","376734","su00prediction","su00whatnext","ultis01adaboost","bergmark02focused","craswell01effective","dlrg02background","haveliwala02evaluating","457229","rigoll99statistical","snoek02stateart","409432","eiter00data","wijsen99stringbased","maloof99machine","455961","ryu01application","hunter00merging","green01sdlip","vanwelie00patterns","388587","pal02web","454519","roth01relational","naumann01from","340329","508859","531549","giorgini01multiagent","ghani01hypertext","472783","antifakos01exploration","kakas01abduction","rosales00hand","322267","489313","vandertorre01contextual","parker00current","fuhr01digital","303350","mitzenmacher01estimating","249633","29745","84828","murphy01bayes","373513","kriegel00managing","afrati02answering","convey01data","li01minimizing","458600","495550","calvanese02lossless","504171","romer01smart","532672","539420","finney02learning","278114","415300","196762","oyama01keyword","williams01searchable","416413","dey01distributed","510172","455655","475379","taniguchi01mining","456004","486097","75800","flake01towards","bartoli00online","454124","caropreso00statistical","boutilier01partialorder","sycara95using","clifton01privacy","tsoumakas01fuzzy","351802","69807","zheng98integrating","norrie02webbased","stockinger01design","vavouras00modeling","stanley01evolving","yong01cooperative","muller01cube","luo02hybrid","timm01from","marsh01evaluating","marsh01guiding","okamoto02supporting","blok00top","windhouwer01flexible","60136","453969","441527","441927","443686","447337","randell02well","510071","202510","315153","wang00argumentationbased","joho02hierarchical","cohen00learning","arpinar00open","brandes01visual","gullickson98using","krishnamurthy01dynamic","michaud01using","kolp01architectural","537667","athitsos01appearancebased","bass01glimpse","406866","403850","kalfoglou01integration","wagner01xmlbased","horn01ai","465022","391515","ormoneit01learning","lienhart02localizing","howell98learning","howell98towards","howell99gesture","turk98moving","bonchi01web","267537","sun99hybrid","sun99symbol","low01simulated","hsu02genetic","530008","maedche02bootstrapping","guestrin02algorithmdirected","crabbe01multiple","383150","carkacioglu02learning","tsuda00subspace","nambiar01benchmarking","zambonelli01emergence","ciancarini02coordination","cakmakci02context","453199","sintek01using","sparkman01automated","532865","inza99feature","smyth01data","kang01qrtdb","483730","vogel01performance","aiello01ontological","deloach02analysis","gottlob02monadic","ianni01intelligent","buffet02adaptive","prodromidis99comparative","483769","setzkorn02evolving","dam01antitonic","fjeld99designing","527235","528700","529964","peng01automatic","484682","ragsdale00adaptation","454034","kim00heterogeneous","lam01overview","vogt00how","gandon02multiagent","527640","470087","hindriks00architecture","539922","meier01towards","reijers01requirements","537176","232896","bartoli02nonlinear","devedzic01knowledge","ben-ameur02multiitem","jalali-sohi01integrated","jalali-sohi01multimodal","roth01scalable","slivinskas01adaptable","lutz99complexity","estlin98using","veloso94learning","krisnamurthy00intelligent","533604","zini01caselp","533891","ali98implementing","nareyek00intelligent","bergamaschi98semantic","424127","camacho01mapweb","oyama00cooperative","pynadath99toward","parsons98argumentation","380343","492009","soderland01building","rosales99trajectory","491341","wactlar00informedia","bellatreche00what","406717","bartolini01feedbackbypass","popescul00automatic","32215","collier99genia","friedman01multivariate","gotoh00language","306088","bertelsen99augmenting","mertz00pushing","artale00expressivity","surmann00five","jansche01information","cardie99integrating","346889","456508","538247","shkapenyuk01design","66638","amato99probabilistic","bohlin00path","12060","wijsen01query","omlin98equivalence","194227","360736","ahanger99technique","jaimes00integrating","slaughter00open","flach99firstorder","jonsson00planning","simmons00first","li01webdocument","mortazavi-asl01discovering","441105","kotagiri01transaction","labrou99interoperability","210930","bellardo00implementing","eiter00difference","drummond97using","337032","thomas00creating","458208","535887","511540","amitay00incommonsense","bailey01engineering","guillaume02web","menczer02topicdriven","rocha00biologically","528932","460643","joseph01why","275630","460958","cunningham01developing","esteban01using","he00comparative","nahm02text","zhao02criterion","68623","89879","degiacomo99incremental","kennedy98anomaly","kennedy99distributed","185650","chakrabarti98scalable","zavrel00information","sachdev98exploration","sachdev98spatial","444471","middleton02exploiting","312028","grahne01algebraic","hammer99information","su00replicable","107700","couvreur99speaker","520409","421280","isokoski01model","300584","251052","mk00implementing","535484","srinivasan02web","radev02probabilistic","baltsavias00integrating","5234","73259","75123","77029","globig95learning","iglezakis00towards","petrak95objectoriented","tammer96learning","362539","tari00cache","47700","440239","418446","449668","502499","11805","375693","ambite01fast","307463","444362","445103","ambroszkiewicz99agent","amin02towards","huget02desiderata","534081","bowman01hybrid","292710","510049","443805","257460","klesen00exploiting","prendinger01social","320482","485564","mayol00wearable","532227","arampatzis00term","lin01indexing","385259","dix00impact","dix00multi","arleo99neuromimetic","kokku02halfpipe","392483","445235","298502","mertz00influence","auer00hybrid","537391","454312","455229","252229","choi00randomized","choi01probabilistic","532291","reddy01coordinating","bentley99three","70863","82834","barros97integrated","410405","flamm01barrier","emmerich00software","saif01communication","bauer00programming","son02qos","tandler01software","sure02ontoedit","schmidt00novel","441239","446289","25137","291240","305534","420817","hustadt00verification","455692","bergamaschi01mobile","gelati01agents","369356","dixon00resolutionbased","502274","chothia01distributed","spelt99theorem","claypool01sangam","nielsen00designing","bettini01xklaim","529556","532128","536016","540380","flake02selforganization","leung01towards","srinivasan02target","sun01world","102637","dautenhahn99bringing","youll00impulse","schuster98neural","smola01regularized","537127","sherrah00fusion","507172","deraedt01three","deraedt98three","szummer02partially","526525","palacz99isomorphism","pelillo99continuousbased","potter01heterogeneity","schuldt99transactions","272797","bonnet00query","gallwitz98erlangen","540663","bowling02multiagent","bradford99characterization","32746","lisetti00automatic","jenkins00primitivebased","brandt01antisocial","braumandl00functional","531713","jonker01temporal","johnson00affectively","535112","gomoluch01information","493991","baek01cost","corradi01policy","jain00comparison","117999","128239","165504","319653","362175","452308","454190","455752","455785","500641","509713","517801","520488","527578","534078","537134","funkhouser02search","godbole01document","lempel01picashow","lin02discovering","mcgowan02who","park01analysis","soundalgekar01internet","thies02searching","488525","stevens01oiling","115390","kadobayashi98seamless","bruni01two","milicevic00socratenon","443654","bryson00hypothesis","wermter01emergent","obitko01ontologies","337690","buneman98equality","490051","burnett01forms","399430","467024","531754","giunchiglia01tropos","winikoff01simplifying","333040","538003","528220","449211","498960","schimkat01maintaining","beimel99oneway","prendinger00hyper","nottelmann01mind","artale02temporal","franconi00general","ho01economic","cantu-paz00combining","348716","533789","536579","carvalho00genetic","casillas01different","506993","stocky02conveying","444527","527187","530219","modha00clustering","santini01query","502516","chien01ecient","galanis01following","jiang02path","34291","maneewongvatana99analysis","domingos99metacost","smith00neural","chiueh99charm","mcguinness00conceptual","llirbat01filtering","madden01fjording","chen01detection","346630","537581","sycara98context","widyantoro99dynamic","crutchfield99evolutionary","128910","cho00estimating","cho02parallel","gal01managing","abdennadher00experimental","ciravegna01lp","459183","366926","488171","417409","307090","531929","codish98widening","king98practical","coellocoello99updated","schallehn02extensible","443913","452812","coppin01reality","445591","457569","critchlow00datafoundry","galhardas01improving","336904","cummins99language","bellavista01how","435716","84358","74893","529138","494121","445758","decker01extending","243755","vincent01agent","17752","bilgic97risk","bilgic97system","decker98coordinating","obrst97constraints","prasad96offline","wagner99toward","weiss99achieving","tran00videograph","castillo99gpropii","261630","degaris00simulating","degaris99evolving","joslyn99semiotic","502491","186486","30500","446625","507954","knublauch02extreme","tveit01survey","higgins99integrated","cox99model","freitas98pkdd","amin02dynamic","cicirello01ant","474192","garcke02classification","463357","broersen01boid","lopez01framework","rahwan00virtual","504568","baldoni00intentionguided","232607","chen01optimal","kargupta01mobimine","libkin99power","tews02gday","536952","536996","316446","du98vulnerability","dubois00augmented","duch00eliminators","duch98optimization","dumais01optimizing","gurret99basis","tawfik01temporal","540845","dwyer99flow","manolescu01microworkflow","kumova00flexible","251444","366169","488116","eriksson98to","altamura00transforming","387378","455694","458630","dempski99augmented","458790","bradley98mathematical","289242","khanna01computing","kosch99managing","bauer01design","377458","bertino99conceptual","consortium00corporate","462285","feris00tracking","wang99ssuptree","521000","438351","291837","kobsa99adapting","446538","373023","fjeld98graspable","489180","36645","525378","79013","schulte99spontaneous","omer00javacorba","boyack01information","eliassi-rad00instructable","grishman01adaptive","ray01representing","265990","539286","ileperuma01mpeg","tauber00localebased","527800","327456","442794","fan01splitting","namee01proposal","moreau00mobile","44892","grasso99augmenting","346939","flake02extracting","71092","266462","goguen00overview","weiss99multiagent","273716","parthasarathy01tackling","cohen01equix","kan01domainspecific","449876","gouveira98feasibility","477302","pfister98room","445880","38463","panzarasa02formalizing","grignon99configuration","525023","jennings01aspects","531878","531895","grundy01software","303146","melin01atlas","cussens99loglinear","vandendoel01foleyautomatic","riley00behavior","mao01adaptivefp","zhu98line","hannebauer99composable","hannebauer99dynamic","harel00characterizing","sastry01cluster","sastry01efficient","pelikan99parameterless","alberto00pattern","hatzilygeroudis02multiinference","prentzas01webbased","prentzas02webbased","457806","mateer99highlyavailable","evans01itr","robbert01astrolabe","499374","herbrich99support","445175","533894","hermansky99temporal","hero99estimation","26655","535578","460628","530815","gomes02versus","suthers01collaborative","sturm00firstorder","511280","leonhardi99virtual","holden99adaptive","feiner99importance","304865","315280","457393","300668","308770","340027","schaller99objectivitydb","273596","straccia01reasoning","433736","520300","svidzinska01world","406330","huang01appliance","kiciman00using","huffman95flexibly","527452","pirjanian00campout","200824","525666","xu01agentbased","227347","nehaniv99constructive","itti99comparison","itti99learning","deligiannidis02dlove","salvucci00intelligent","231484","filliat99incremental","307172","383856","bridge98defining","filliat00active","441373","239748","445127","panzarasa01social","tambe00adaptive","wu00selfsupervised","497508","wang00experience","459887","525119","445220","magoulas01hybrid","plagianakos01tumor","folch00typtex","510100","frank99naive","kurimo99latent","lam00broadcasting","lam01broadcasting","stockinger01towards","459526","bourdeau99three","davison98applying","rasheed98adaptive","rosenfeld00two","467998","509024","scerri99ease","malec00implementing","prokopenko00cyberoos","robinson99requirement","knight01visualisation","469172","mann02testing","243743","lacher01facilitating","311589","503542","510434","wachsmuth01lifelike","420411","touzet01side","bonchi01data","punin01web","302729","306507","bozzano99logic","539207","508515","509627","arimura01efficient","487737","behringer98improving","311786","koskela00picsom","distefano01coordinating","dragoni00mental","dipietro99experiences","bird01olac","landau02comparison","daelemans97featurerelevance","langley95acquisition","162298","giraud-carrier98beyond","415731","viegas00collections","krum02speech","524967","snyders00confseek","kalganova99evolving","339430","467320","533620","marin01hybrid","67194","73250","449513","garland00learning","miller01training","316064","weber00viewpointinvariant","vanhoof99bottomup","524920","104045","kallmann99behavioral","chiu99meta","li99multifaceted","liechti00digital","pantic00expert","449007","kusiak01galgorithm","40506","grimm00revisiting","roy00finding","keim99proverb","liu00learning","24678","82903","fraternali98proceedings","liu01rulebased","liu98logical","liu99partial","wuwongse01xml","443668","ljungstrand00analysis","hoque98information","lueg00information","457459","460214","gouveia98end","464721","294630","papadias99constraintbase","raskar01interacting","453805","glance00community","xie02locality","508816","ashbrook02learning","509693","marques02componentbased","emmerich99incremental","matthews00fuzzy","lauzac01view","404966","mcbreen01evaluating","455346","meuss99improving","496354","539185","3489","ardissono00plan","ardissono96uso","mcroy98achieving","traum99speech","zhang99query","althoff99using","meyer99constraint","293552","208788","mihalcea99word","493671","526346","papaioannou01manufacturing","aroyo02layered","240825","crabtree98wearable","mohan01efficient","460667","453210","zhang01efficient","314563","49194","lomuscio96qlb","271013","campos01searching","goldberg99genetic","537064","cugola01peerware","diehl00vrml","458848","edwards97systematic","palen99social","461789","scholer02compression","243029","kruegel02distributed","pouzol01from","186241","496719","myers01interacting","evers00jacob","457268","303963","norman96alarms","98937","erni98generic","steiner98omsjava","20419","27008","95715","nrvg99persistent","nrvag99vagabond","428316","oard01clef","503243","singletary01learning","olson00probabilistic","olson99subpixel","12247","caputo01from","ordonez01mining","oria99visualmoql","hightower01survey","34099","pandurangan02using","505987","532537","paradis98language","paradiso00footnotes","williamson00foundations","norman00argument","schroeder01fuzzy","dey99conference","dinn99active","steel02finding","464421","515869","jennings99robust","pavlovic96gestural","sharma96speechgesture","triesch98gesture","tsap01feedback","vardy99wristcam","266823","miagkikh99generalized","phan02extensible","skow02security","piater00distinctive","taylor99virtual","437003","531861","busi01some","pinheirodasilva00umli","pirjanian99behavior","472493","ardissono01tailoring","abraham00hybrid","hightower01realtime","bakker01lart","demeer00programmable","puliafito00using","215383","wang01process","243827","257383","270678","318212","478335","485557","487698","aiken98abc","cavedon95logical","cavedon95revisiting","debenham99multiagent","ehlert01intelligent","ehlert01reactive","elio00task","morley96semantics","norling01learning","pollack99adjustable","wooldridge96logic","wooldridge96practical","mandl01topographic","360831","fjeld99exploring","269982","germans01virpi","454762","119642","540061","bazzan99moral","460612","rosenthal01administering","abonyi00structure","abonyi01modified","abonyi02datadriven","45929","rousseau97improvisational","235157","frey99estimating","326373","roy00computational","532267","claypool99optimizatizing","gaudiano99neurobotic","59359","jantke95communications","lopesdeoliveira99framework","sampaio00design","295735","yokoo02secure","518526","513722","475504","327415","hahn98ontology","539227","354467","499517","schweighofer01improving","454621","zhang01personalized","adya00generalized","shapiro99snep","lerman00coalition","303620","376260","tomsich01optimizing","449447","sloman01varieties","sloman98damasio","480065","23780","42037","215779","rafter00automated","308750","chen98learningbased","298012","stanoi99decentralized","mayol02designing","schiele99situation","531526","388718","450405","396385","155240","sun01individual","301891","480233","539969","524726","luyten01xmlbased","534400","508732","532373","381995","timm01enterprise","tourapis01temporal","tan01infocockpit","537920","tzouramanis01time","tzouramanis99processing","gimbel01data","482071","496883","tan01trust","valencia98hitch","540018","vasconcelos00bayesian","vilalta01rule","66053","bryce99coordination","502642","309072","461165","wang99negation","swindells00system","ware00rotating","293457","gabbard97taxonomy","meng98data","warshaw01facilitating","weiss01predicting","208646","458592","162738","wilke96framework","205160","409610","wittner00network","508492","gendelman00fast","defago00totally","346876","williamson00random","wills01open","yeates01memory","442161","dejong01multilayer","wolski00design","vazov01system","529980","self01design","xu02modeling","jennings00implementing","332262","athitsos01hand","li01characterizing","30494","206485","70288","cremers00diffusionsnakes","kervrann00level","yu01indexing","federici95advances","344548","zhang01evolutionary","zhang99towards","zhao99discriminant","vonhardenberg01barehand","content","paper_id of content","paper","word_cited_id of content","word1163","word1509","word1614","word1642","word1663","word1798","word1843","word1989","word2026","word216","word2400","word2457","word2522","word2598","word2619","word262","word2642","word2903","word3017","word3051","word3164","word3269","word3273","word3288","word3412","word3448","word3670","word37","word47","word566","word66","word103","word1030","word1161","word1330","word148","word1512","word1584","word1606","word169","word1916","word1988","word2066","word2086","word212","word2217","word2267","word2285","word2375","word2430","word2469","word2475","word2545","word2569","word2571","word2595","word2610","word2700","word2718","word2977","word2978","word32","word3204","word411","word506","word544","word580","word651","word901","word982","word1039","word1055","word1173","word1270","word1277","word132","word1489","word1546","word167","word1707","word1739","word19","word2151","word2345","word2532","word2564","word3005","word3123","word3146","word3404","word3488","word3502","word3555","word3615","word602","word614","word740","word809","word88","word945","word1262","word1266","word130","word1302","word176","word1847","word2238","word2240","word2242","word2264","word2355","word2396","word2690","word2699","word2715","word2953","word3035","word3089","word3135","word3137","word3150","word3360","word3378","word3600","word3633","word494","word564","word866","word1047","word1091","word1099","word1238","word1286","word1612","word1734","word1768","word1884","word1937","word197","word2251","word2311","word2452","word2540","word2577","word2737","word3193","word3232","word3279","word3323","word3371","word3450","word3610","word54","word620","word746","word817","word825","word858","word958","word990","word115","word1178","word1583","word170","word1738","word2","word2124","word2144","word2173","word2458","word248","word2605","word287","word3191","word328","word3565","word59","word76","word832","word918","word979","word1240","word1245","word1246","word1303","word1362","word1549","word1561","word1569","word1619","word187","word1894","word1938","word2011","word2277","word2526","word2719","word2742","word2869","word2931","word3018","word3347","word3391","word548","word732","word798","word799","word815","word1071","word1192","word1556","word1624","word1636","word1720","word1726","word2246","word2344","word2461","word2476","word2539","word2751","word2753","word2820","word2964","word3056","word3176","word33","word3325","word3335","word3346","word370","word401","word42","word582","word879","word994","word111","word134","word1983","word22","word2216","word2234","word2336","word2352","word245","word2559","word2841","word2921","word3236","word3289","word3366","word3658","word632","word753","word2166","word235","word2356","word2403","word2566","word2616","word2665","word2691","word2734","word3640","word3641","word402","word1357","word1423","word1625","word1741","word1985","word2109","word223","word2444","word2460","word2499","word2575","word2582","word2687","word2746","word279","word2928","word2966","word3069","word3113","word3322","word337","word3541","word554","word625","word730","word847","word868","word1076","word1079","word1184","word147","word174","word1834","word1893","word2171","word2189","word2209","word2551","word2885","word3031","word3160","word3379","word3380","word3498","word3585","word3657","word374","word538","word638","word640","word765","word807","word1517","word1524","word1605","word1618","word1632","word1645","word1743","word1758","word201","word2050","word209","word2114","word2279","word2281","word2975","word3131","word3261","word3311","word3317","word419","word433","word508","word511","word13","word1635","word1982","word2529","word2554","word2741","word2886","word2923","word3048","word3049","word3127","word3185","word3396","word3473","word351","word3523","word3525","word3573","word387","word39","word560","word687","word929","word965","word976","word1009","word1234","word1323","word1761","word2078","word2112","word2192","word2340","word2837","word2853","word3020","word3109","word3648","word397","word553","word561","word763","word834","word853","word988","word101","word1088","word1185","word1206","word1231","word1290","word1776","word1929","word2145","word2227","word2404","word2628","word27","word2705","word2926","word2989","word301","word3059","word3206","word3334","word3430","word3503","word3515","word3558","word386","word413","word463","word510","word517","word592","word764","word97","word1022","word1158","word1562","word1694","word1737","word1869","word1969","word1976","word2728","word281","word425","word533","word760","word820","word1263","word131","word1566","word1611","word1620","word1750","word238","word2389","word2516","word2822","word2830","word2852","word307","word3426","word434","word679","word806","word813","word124","word1251","word1318","word1488","word1533","word1700","word1722","word2012","word230","word2303","word2386","word246","word2548","word937","word1069","word1189","word1378","word1589","word1756","word1809","word1964","word1978","word2169","word2299","word2622","word2637","word2640","word2653","word2684","word2720","word2941","word2994","word3040","word3252","word3554","word543","word636","word139","word1570","word1594","word2082","word2291","word2511","word2521","word2586","word3231","word462","word512","word805","word983","word1094","word1193","word1227","word1361","word1513","word1526","word1571","word1764","word1826","word2135","word2190","word231","word2449","word2814","word3250","word3258","word3614","word644","word83","word1038","word1111","word1123","word1654","word2140","word265","word2787","word2813","word2912","word3471","word45","word626","word974","word1050","word1164","word1434","word1441","word1560","word1686","word1971","word2301","word2307","word2378","word2533","word300","word3046","word3229","word3458","word536","word882","word966","word1275","word1380","word1417","word1580","word166","word1703","word2487","word2721","word2749","word289","word3214","word3397","word491","word546","word605","word995","word1242","word1421","word1431","word1575","word1782","word1996","word2187","word2265","word2431","word2613","word2644","word2658","word2769","word2786","word28","word2927","word2983","word2997","word3013","word3111","word3224","word3477","word3512","word460","word534","word56","word58","word1472","word1621","word1735","word1831","word2029","word2062","word2063","word207","word2093","word211","word2180","word222","word251","word2581","word3536","word40","word426","word675","word709","word1042","word1305","word1547","word1631","word17","word2274","word2343","word2437","word2491","word2600","word2661","word2706","word2868","word3190","word3468","word456","word555","word601","word877","word89","word1","word1012","word1064","word1383","word1788","word1910","word1932","word2328","word2587","word2757","word3278","word673","word700","word950","word1105","word1333","word1344","word1579","word1933","word2490","word257","word2847","word3341","word3414","word3572","word482","word658","word790","word854","word1049","word1151","word1205","word1214","word1396","word14","word2199","word2273","word2410","word2507","word3542","word427","word1211","word1339","word1427","word1516","word1653","word1832","word1919","word2498","word250","word2920","word3166","word3259","word1159","word1183","word1304","word2186","word2228","word2377","word249","word2601","word2992","word3645","word783","word1098","word1157","word1797","word1902","word1917","word2038","word2871","word2936","word3314","word3672","word3690","word381","word388","word547","word836","word1067","word1083","word1121","word1281","word1461","word208","word2172","word2302","word2331","word2484","word2657","word3084","word3184","word530","word542","word951","word1109","word1252","word1280","word1437","word1463","word1598","word2037","word2387","word3478","word604","word630","word657","word842","word1005","word1201","word2203","word2366","word243","word2480","word2674","word2735","word616","word621","word1090","word1188","word1218","word1871","word2104","word2220","word2225","word2235","word2288","word2702","word2767","word312","word3499","word572","word615","word655","word74","word767","word77","word100","word1015","word1398","word1923","word2232","word2233","word2435","word2611","word2736","word2819","word2880","word3087","word334","word3463","word772","word921","word1250","word213","word2305","word2714","word3383","word635","word754","word964","word996","word1308","word1425","word1787","word1949","word2005","word2358","word2664","word2692","word3016","word43","word446","word466","word518","word1132","word1187","word1309","word133","word1336","word2370","word2681","word2747","word3093","word1160","word1796","word2413","word2520","word254","word2724","word2870","word295","word3493","word1044","word1081","word1668","word1728","word2255","word2542","word2609","word3083","word3286","word3508","word1568","word1582","word1616","word2398","word2506","word3149","word444","word642","word750","word827","word1387","word1780","word2339","word2434","word2680","word2727","word3507","word3559","word571","word583","word591","word737","word757","word952","word1664","word1950","word2003","word2615","word3318","word3483","word584","word812","word986","word1690","word178","word2025","word3066","word371","word44","word889","word1101","word126","word1301","word1518","word1529","word1567","word1772","word1979","word1994","word2004","word2341","word2472","word2888","word3553","word3580","word3606","word535","word823","word913","word1315","word1355","word150","word205","word2393","word2546","word2900","word2980","word3116","word390","word483","word78","word1253","word1363","word2839","word3102","word3120","word3141","word322","word472","word681","word1216","word1456","word1727","word2259","word2367","word272","word2858","word3233","word3350","word3561","word357","word429","word445","word520","word713","word1322","word1326","word1563","word2256","word2258","word2292","word2573","word2585","word2662","word2823","word3007","word308","word3428","word377","word773","word1578","word172","word1999","word2243","word247","word2602","word2799","word3161","word3331","word3408","word49","word1085","word136","word1875","word2092","word2094","word3186","word3189","word3516","word3655","word409","word874","word1017","word1041","word1155","word1195","word1283","word152","word1600","word23","word2812","word3036","word610","word941","word1108","word1139","word1835","word1886","word2326","word3153","word3301","word3479","word574","word1016","word1097","word1135","word1603","word1607","word1838","word227","word30","word3151","word3386","word3538","word589","word894","word1061","word1197","word1403","word1588","word1638","word1941","word1991","word1998","word2524","word2596","word2807","word286","word3403","word579","word595","word597","word599","word720","word725","word745","word771","word896","word2106","word2183","word3078","word420","word559","word1040","word2032","word2639","word2723","word338","word3442","word1352","word1914","word2130","word2268","word2388","word2417","word2510","word2519","word2553","word2562","word3500","word3543","word410","word490","word587","word939","word1984","word2593","word3042","word3244","word3337","word481","word526","word1419","word171","word2283","word2411","word3145","word618","word922","word2061","word2174","word2432","word540","word981","word2168","word226","word2310","word306","word3061","word3438","word857","word969","word1629","word1704","word1874","word2058","word2479","word2495","word3292","word3367","word3497","word480","word1029","word1033","word1410","word1530","word2031","word2113","word2121","word2732","word3411","word598","word802","word1907","word2165","word2574","word2672","word2693","word2791","word3014","word3481","word624","word875","word1706","word41","word1127","word1153","word1272","word1715","word1800","word1930","word2621","word3015","word305","word346","word467","word586","word647","word680","word774","word90","word1114","word1243","word183","word2357","word2422","word2423","word2560","word2917","word3492","word369","word884","word1093","word113","word1181","word1646","word1896","word1992","word2412","word3147","word723","word1215","word2184","word2270","word2315","word2456","word2492","word2859","word2958","word435","word471","word752","word1811","word1951","word2248","word3480","word3547","word3604","word237","word3578","word603","word617","word694","word1170","word1436","word2907","word3148","word3608","word606","word810","word1615","word1957","word2462","word2722","word3517","word3518","word1089","word1212","word1494","word1623","word194","word2236","word2790","word347","word3482","word864","word1581","word1852","word1931","word229","word2636","word2750","word3012","word3200","word3227","word567","word1073","word1077","word1507","word1604","word1637","word1820","word1877","word2231","word225","word2558","word2892","word3000","word3597","word712","word987","word1106","word2261","word2402","word2450","word2709","word2711","word2716","word2796","word2815","word3158","word3303","word3382","word3586","word833","word180","word198","word1980","word232","word3194","word3571","word3607","word759","word841","word1746","word1861","word2369","word2547","word2703","word2773","word2985","word1080","word1854","word1954","word2042","word2493","word2525","word2648","word3050","word489","word1084","word1104","word1498","word1542","word122","word2014","word2390","word2940","word2967","word3003","word3464","word485","word1313","word1643","word1660","word2407","word2677","word2764","word1449","word1487","word1534","word1565","word1596","word3504","word611","word1786","word1905","word2654","word3271","word35","word3613","word2731","word2895","word3091","word3328","word3348","word455","word955","word2864","word2893","word3006","word314","word3175","word686","word1074","word1122","word1763","word29","word3180","word1202","word1540","word2206","word258","word2782","word2795","word2949","word2972","word3096","word3183","word594","word1298","word1724","word1789","word2088","word3201","word3549","word529","word1952","word2132","word2860","word36","word784","word830","word1424","word1774","word2000","word2263","word2810","word291","word3071","word3156","word3316","word3528","word3674","word3687","word531","word57","word70","word839","word909","word1107","word1501","word1673","word2059","word2150","word2195","word430","word509","word919","word1909","word252","word2939","word2950","word3088","word3251","word3374","word3624","word3677","word3685","word736","word1519","word1939","word2156","word3170","word3643","word2754","word3349","word3392","word3569","word3693","word415","word710","word845","word923","word940","word123","word2207","word2453","word2527","word1119","word1842","word2408","word2876","word3587","word3595","word384","word408","word1223","word1320","word1426","word1485","word1771","word210","word2245","word2296","word3155","word3566","word3629","word1340","word1997","word1310","word2478","word2666","word2935","word717","word782","word1056","word138","word1493","word2006","word2846","word2973","word3019","word3501","word628","word1766","word2247","word2770","word748","word1977","word2129","word2879","word3199","word61","word789","word846","word881","word984","word200","word2485","word2744","word2792","word1895","word3652","word867","word1103","word2035","word2142","word3255","word3513","word3526","word948","word162","word2579","word2087","word303","word3243","word3304","word609","word1393","word156","word2108","word2250","word2738","word668","word972","word985","word989","word1258","word1364","word1457","word1657","word1723","word233","word3268","word3491","word792","word936","word2503","word2531","word2838","word2914","word321","word3495","word848","word1006","word1035","word1086","word1143","word2297","word2406","word255","word2824","word297","word3","word3159","word3656","word452","word575","word72","word829","word107","word1683","word2322","word290","word856","word1024","word1175","word1775","word2119","word2349","word2818","word3126","word504","word999","word1241","word1466","word1521","word3680","word662","word758","word1990","word3340","word3694","word1060","word3357","word1495","word192","word2218","word3363","word3695","word1138","word1268","word1676","word1912","word2784","word3118","word3576","word3682","word46","word473","word949","word1256","word1544","word1572","word1967","word3618","word1046","word1342","word1379","word1450","word1751","word1822","word2117","word2309","word292","word3418","word50","word762","word855","word1236","word1446","word1558","word2001","word2221","word2991","word1317","word1882","word1898","word2638","word3130","word3470","word3654","word840","word1054","word1194","word1928","word1968","word3356","word1013","word1026","word1239","word1347","word1841","word2056","word2514","word2910","word2974","word499","word549","word1196","word1259","word1411","word2055","word2176","word2185","word2625","word276","word3054","word3063","word3213","word3275","word3358","word3520","word362","word696","word165","word2158","word241","word3068","word3073","word403","word96","word1324","word2804","word3235","word3339","word361","word515","word928","word1008","word2318","word2854","word2170","word2768","word2777","word2845","word3496","word1608","word1753","word2363","word2947","word3181","word86","word1021","word2471","word2501","word2509","word354","word3574","word600","word791","word957","word975","word1130","word1731","word1881","word1927","word1960","word2272","word2324","word3454","word447","word1392","word142","word1451","word1749","word2325","word3074","word3098","word3575","word79","word1235","word2319","word2682","word2878","word3110","word1037","word1096","word1291","word1351","word1474","word1543","word2084","word2942","word818","word1358","word1359","word1514","word1515","word1785","word2289","word2300","word2316","word643","word151","word1719","word1922","word2534","word3154","word3683","word372","word1229","word1247","word1574","word1595","word2269","word2651","word3527","word747","word1065","word1552","word2428","word2809","word3665","word1350","word2208","word2368","word288","word3197","word3310","word1307","word1587","word1799","word1828","word2040","word2071","word2866","word458","word556","word1429","word2074","word2085","word2380","word324","word3313","word3424","word3589","word645","word1497","word2726","word2763","word3132","word1576","word2182","word240","word2901","word3142","word3596","word366","word664","word1070","word2517","word2643","word2881","word850","word998","word2294","word2306","word2401","word2429","word266","word2801","word3171","word899","word141","word1745","word1747","word2054","word2125","word2252","word2505","word2887","word3285","word3307","word3455","word1468","word2685","word671","word2583","word2758","word1152","word2134","word2971","word1343","word2604","word663","word1124","word1348","word1866","word1880","word2018","word2445","word2865","word3329","word487","word513","word677","word915","word1550","word1655","word2060","word708","word203","word2308","word3058","word3152","word396","word585","word776","word1394","word1597","word2007","word268","word3008","word3219","word3389","word1825","word2249","word382","word502","word911","word931","word2347","word2840","word3001","word318","word766","word831","word1844","word2191","word2332","word437","word608","word978","word108","word1539","word1688","word1689","word1784","word3075","word3266","word344","word920","word1740","word3669","word1972","word2103","word3605","word12","word1341","word2835","word2987","word684","word106","word862","word2836","word1935","word3617","word1687","word3207","word1299","word1447","word179","word1824","word1860","word1892","word2229","word2761","word3104","word501","word1028","word1115","word2072","word2439","word2572","word3112","word431","word666","word729","word769","word819","word2143","word215","word220","word25","word302","word3239","word3336","word3602","word414","word69","word1169","word1452","word1628","word2568","word2588","word2924","word3026","word3139","word1335","word816","word942","word1701","word1708","word1867","word2076","word2634","word283","word3638","word38","word468","word963","word1031","word1145","word1375","word2016","word2863","word3041","word1827","word2138","word120","word1148","word1328","word1462","word2091","word2212","word75","word1249","word1420","word1925","word2047","word2361","word2483","word2584","word261","word2776","word3423","word1864","word2857","word2986","word339","word497","word304","word716","word1484","word863","word1500","word1659","word2105","word2438","word2443","word3209","word3225","word3226","word1345","word1353","word2312","word2470","word2515","word2676","word2725","word2849","word3212","word3388","word665","word2913","word2968","word568","word1440","word1454","word1765","word1900","word2064","word2202","word2409","word3345","word646","word1066","word1131","word1381","word1656","word3202","word1354","word2204","word2381","word2984","word860","word1414","word2329","word360","word3647","word404","word1564","word181","word3534","word1672","word1680","word1995","word1733","word3353","word883","word1889","word2816","word3099","word3564","word3628","word562","word702","word1602","word278","word1374","word146","word1555","word2563","word3490","word3577","word1068","word1408","word1443","word1732","word214","word469","word1483","word2099","word593","word2164","word2463","word1180","word1332","word1666","word1987","word3432","word690","word778","word821","word2075","word2133","word2237","word2362","word3466","word558","word734","word1821","word2359","word2918","word648","word926","word1020","word1801","word2080","word450","word890","word1499","word2089","word2828","word3474","word938","word991","word116","word2694","word3274","word3510","word707","word1207","word1593","word1897","word2020","word2829","word3077","word3368","word3369","word3456","word1386","word1545","word2354","word2673","word3076","word660","word2618","word336","word418","word1956","word1961","word2222","word3413","word3422","word110","word2448","word3673","word1942","word2057","word2379","word453","word524","word682","word1532","word1948","word2929","word1851","word2323","word486","word793","word528","word557","word1260","word1400","word1590","word1626","word2148","word2152","word2374","word1699","word182","word1846","word2488","word3257","word3332","word63","word718","word1432","word2696","word1478","word1908","word2911","word2993","word3108","word3460","word652","word698","word1311","word1671","word2346","word2556","word3668","word421","word60","word2502","word3621","word828","word2188","word91","word1210","word1261","word1430","word1470","word2224","word2244","word2474","word353","word443","word814","word885","word1149","word1282","word143","word1522","word1627","word1695","word1718","word407","word785","word1541","word2280","word3122","word3027","word3246","word1072","word1219","word1418","word2567","word313","word102","word1186","word1911","word2877","word3390","word442","word796","word3486","word962","word1045","word1062","word1292","word1553","word2844","word3393","word358","word373","word1401","word196","word465","word496","word1294","word2962","word3627","word498","word1617","word2590","word3044","word1010","word2875","word2919","word3445","word808","word943","word2102","word2934","word3410","word3469","word383","word1027","word1213","word1857","word1936","word2629","word3254","word654","word1120","word1327","word244","word2740","word26","word1092","word218","word2350","word2831","word741","word1779","word3352","word92","word2149","word2447","word3312","word861","word2391","word3326","word1585","word1691","word2053","word3441","word3623","word464","word550","word1870","word2530","word3681","word1721","word3425","word2123","word3222","word661","word1438","word1491","word3287","word3372","word34","word3407","word393","word55","word1508","word2147","word2159","word2257","word1848","word519","word1125","word2271","word2979","word3678","word1681","word273","word1334","word1698","word2317","word3612","word1204","word2607","word2925","word294","word1389","word3100","word3208","word1338","word163","word2550","word2873","word3136","word3264","word1503","word53","word85","word1476","word590","word3447","word3650","word492","word1118","word1365","word2365","word2441","word3119","word3327","word484","word2313","word2756","word3045","word3530","word2017","word2455","word3702","word581","word695","word155","word2065","word3433","word350","word751","word2867","word340","word3485","word3661","word2436","word2667","word2276","word2855","word722","word1453","word3272","word1435","word1018","word565","word835","word1136","word1559","word1591","word188","word1921","word2295","word2440","word2701","word2739","word676","word109","word1397","word2399","word2486","word2589","word3114","word476","word659","word902","word1032","word705","word2097","word925","word1141","word1265","word1464","word1652","word2219","word2874","word514","word1019","word2771","word3125","word343","word930","word1973","word461","word84","word2397","word2842","word541","word2110","word62","word693","word3365","word3676","word3689","word199","word2178","word2695","word2772","word2856","word2896","word3103","word3421","word1254","word3144","word893","word1048","word2821","word3651","word3663","word739","word742","word905","word917","word971","word1225","word1577","word2765","word2817","word3133","word728","word795","word1918","word1963","word2337","word2775","word1288","word3030","word803","word3409","word345","word356","word872","word1142","word1943","word2442","word2898","word3260","word399","word1172","word2538","word299","word3449","word3524","word355","word3660","word633","word3644","word859","word900","word1405","word1802","word2689","word2733","word1633","word2528","word2729","word3265","word569","word1807","word3453","word1220","word161","word1648","word2990","word3439","word3692","word786","word904","word1496","word3195","word944","word2789","word674","word3115","word323","word1036","word1868","word3277","word3283","word1511","word3192","word3376","word637","word1981","word2036","word2177","word234","word2549","word320","word325","word649","word1479","word2083","word3203","word439","word522","word629","word127","word1712","word3395","word71","word871","word9","word960","word1166","word1940","word3666","word1110","word1179","word2162","word224","word3300","word3330","word3593","word715","word128","word2044","word1966","word2843","word516","word1855","word1913","word1390","word1685","word2181","word551","word1147","word3539","word432","word2415","word2214","word428","word1504","word1573","word2193","word2788","word317","word3228","word3557","word1289","word275","word3462","word607","word2200","word667","word125","word577","word924","word2688","word2832","word3168","word3688","word505","word1230","word1274","word1944","word2523","word2623","word440","word844","word852","word1082","word2932","word619","word3435","word596","word1770","word2198","word364","word454","word2107","word3217","word3467","word1137","word2659","word3090","word2333","word2743","word2890","word3522","word1805","word3384","word1285","word219","word3043","word3117","word1865","word2760","word1014","word3302","word3343","word2686","word3032","word3583","word3591","word1675","word1679","word1920","word3622","word1295","word1883","word2048","word400","word2392","word3188","word3440","word1903","word2111","word3086","word3263","word685","word1752","word1778","word117","word2576","word525","word104","word1257","word1428","word202","word3033","word779","word1133","word1150","word173","word236","word2675","word2954","word3134","word3167","word578","word1287","word160","word3298","word3362","word3443","word3532","word1007","word1399","word412","word946","word1975","word2215","word3067","word1873","word3121","word1168","word2894","word3062","word678","word777","word1506","word755","word2614","word376","word2266","word2762","word395","word1947","word2670","word3636","word449","word878","word2862","word3237","word94","word1117","word140","word3065","word3626","word2049","word2645","word2998","word3506","word4","word669","word744","word82","word1709","word2022","word2079","word3105","word691","word1349","word2580","word1176","word3101","word3521","word1682","word2482","word2808","word114","word2766","word309","word3306","word1433","word2284","word1134","word2015","word2785","word3295","word1535","word3230","word3342","word800","word826","word3187","word1448","word2385","word144","word2904","word1490","word2330","word2481","word933","word2678","word992","word2425","word2446","word284","word2944","word3402","word2163","word406","word1384","word145","word1730","word1879","word804","word1710","word1953","word3319","word3333","word887","word2652","word2752","word3182","word656","word770","word2459","word1669","word52","word1662","word2504","word1876","word1075","word3165","word2959","word1003","word2833","word422","word3172","word1538","word2778","word914","word1177","word1890","word2211","word1924","word2131","word2395","word897","word95","word2995","word2327","word2996","word552","word726","word749","word2360","word1970","word129","word2179","word24","word493","word692","word1171","word1273","word1382","word1467","word1815","word2668","word3060","word315","word2656","word367","word521","word1198","word2241","word1237","word1791","word1813","word3025","word3505","word801","word1406","word1677","word1744","word31","word3514","word159","word2451","word253","word2803","word3431","word1209","word2160","word3634","word385","word2120","word507","word811","word1599","word2938","word3653","word997","word1757","word3241","word1520","word164","word697","word903","word296","word470","word2282","word260","word973","word1481","word2254","word2617","word1697","word2253","word3659","word781","word1644","word2081","word1777","word1783","word2027","word3297","word3305","word495","word780","word3052","word3671","word1264","word2697","word1742","word3248","word1370","word865","word1528","word1858","word375","word2034","word2946","word3162","word704","word1862","word3487","word3620","word3639","word959","word2707","word2039","word537","word1455","word1510","word1705","word1808","word2797","word1460","word743","word1471","word886","word3085","word3281","word2426","word2544","word319","word3686","word5","word588","word363","word1759","word2141","word3635","word3691","word1191","word895","word1102","word1221","word1271","word1725","word2096","word2982","word3475","word1385","word2781","word417","word2046","word953","word2070","word3637","word416","word67","word1300","word1853","word2899","word2115","word2806","word2851","word3679","word775","word1144","word869","word3398","word1407","word2730","word2957","word1465","word961","word263","word1904","word2712","word2713","word714","word93","word1651","word2704","word613","word1314","word1377","word1480","word1804","word1887","word2884","word3028","word477","word3174","word2570","word3684","word1001","word333","word2679","word3157","word1609","word3216","word3540","word1830","word3509","word3598","word3632","word1767","word2213","word2956","word3106","word3223","word3590","word653","word1548","word1505","word2095","word2755","word1409","word1658","word1692","word2127","word2128","word2421","word1360","word3370","word2416","word2418","word3601","word1000","word2155","word2774","word2961","word3211","word1934","word2372","word3436","word1395","word1849","word264","word2802","word639","word527","word1899","word2468","word1376","word3399","word2608","word1816","word2759","word2794","word2963","word3420","word3138","word1622","word2960","word3072","word3489","word1116","word822","word1388","word1693","word2045","word112","word3242","word2009","word2320","word2908","word3494","word365","word1226","word1945","word2632","word761","word3055","word1278","word326","word2909","word3361","word2028","word3546","word1228","word3531","word3097","word977","word650","word217","word2915","word3004","word479","word3701","word719","word727","word2287","word2384","word2477","word2223","word3570","word634","word65","word2496","word3210","word1959","word2136","word2606","word1112","word1146","word1475","word3024","word794","word2748","word3163","word3416","word282","word1167","word3355","word2497","word3631","word3256","word1962","word2405","word1002","word1901","word2321","word797","word2798","word3022","word1051","word908","word1885","word1891","word2420","word389","word1445","word2043","word2641","word2861","word3002","word3385","word2051","word2122","word2100","word612","word641","word1058","word3338","word1369","word3220","word3290","word3291","word3359","word3394","word843","word891","word1023","word788","word1955","word398","word1818","word2655","word3140","word1222","word195","word1986","word2889","word733","word876","word1128","word186","word2293","word3405","word3582","word3664","word16","word3344","word259","word532","word689","word1162","word2969","word3205","word1248","word1190","word2286","word1293","word20","word2205","word2671","word851","word157","word21","word2930","word1057","word2290","word2937","word2599","word298","word3533","word2194","word2512","word2427","word3373","word3437","word1442","word2126","word3249","word2030","word3675","word670","word448","word1845","word3095","word1926","word2467","word3092","word1373","word392","word1477","word2592","word51","word3023","word3354","word3535","word3094","word1404","word3284","word1052","word1717","word3169","word3082","word168","word2805","word380","word1444","word2597","word1817","word457","word1856","word1319","word2376","word2594","word2541","word1714","word2010","word405","word672","word1554","word2414","word2793","word1667","word2922","word3064","word3699","word2033","word3568","word1321","word3550","word824","word2708","word3457","word7","word2565","word2780","word149","word1670","word3476","word1087","word285","word1794","word2578","word1331","word3107","word688","word1803","word2933","word2970","word2157","word1312","word175","word2068","word2518","word2008","word947","word2139","word2552","word2683","word191","word3021","word1760","word1974","word3299","word2101","word3070","word3215","word2494","word2669","word3472","word2116","word394","word683","word3321","word3324","word1523","word1140","word3401","word1011","word2364","word1412","word3276","word631","word121","word1795","word2620","word3594","word3609","word711","word1459","word2167","word916","word2146","word2353","word2591","word1859","word699","word1850","word1233","word1769","word2883","word2342","word3080","word2024","word1551","word3662","word73","word1527","word3611","word2201","word1502","word1650","word3563","word2561","word787","word2543","word2196","word2955","word475","word1661","word3592","word2175","word545","word768","word3560","word270","word3128","word1325","word3544","word3484","word8","word68","word622","word837","word2197","word3198","word1833","word2536","word436","word2624","word2371","word2811","word2019","word3387","word3057","word2906","word3642","word1640","word3009","word3129","word3556","word2698","word2988","word1888","word2041","word1965","word2508","word3429","word98","word341","word934","word11","word1366","word1829","word1872","word2226","word888","word1034","word1306","word2537","word349","word1422","word706","word438","word158","word2275","word2783","word1203","word2650","word3417","word177","word2633","word3280","word189","word1025","word1469","word3406","word1297","word2424","word2473","word2500","word2891","word573","word967","word993","word1641","word2002","word954","word1100","word3178","word1482","word335","word1812","word3459","word1473","word968","word424","word892","word3444","word81","word838","word2348","word1958","word2981","word1665","word1814","word1836","word1840","word2710","word3238","word3649","word137","word2278","word627","word927","word1415","word1492","word2260","word1368","word2419","word2649","word1200","word3667","word2098","word2779","word980","word2304","word3173","word539","word1754","word3253","word1367","word1793","word2161","word3038","word423","word1678","word2118","word2466","word2948","word228","word2999","word310","word1610","word2800","word2872","word3081","word379","word1059","word3551","word1915","word2850","word3519","word1182","word1329","word2153","word2210","word3037","word3039","word1458","word48","word898","word118","word2952","word500","word2612","word563","word2052","word2603","word3267","word3427","word3270","word105","word2394","word204","word269","word1296","word3177","word3196","word1413","word2717","word1773","word576","word2298","word3697","word3053","word2489","word3646","word2077","word1174","word221","word277","word2069","word1199","word3567","word1790","word3700","word3696","word1053","word368","word731","word1402","word316","word10","word2513","word1337","word3545","word359","word523","word3511","word906","word1129","word15","word970","word2314","word3315","word2334","word1863","word2916","word1356","word64","word910","word1346","word1906","word190","word1634","word3282","word3245","word330","word1716","word184","word154","word3603","word2023","word1823","word3446","word2013","word1276","word99","word3625","word3529","word2663","word870","word3599","word3010","word1244","word1284","word1781","word2239","word1557","word256","word331","word3375","word623","word1269","word3179","word3703","word1063","word756","word267","word932","word1647","word242","word3296","word193","word3451","word2965","word2090","word274","word3364","word280","word3562","word1806","word2897","word1371","word2660","word3619","word1416","word3537","word2635","word451","word293","word2154","word271","word873","word1126","word488","word2557","word1601","word3029","word459","word738","word2230","word3143","word3079","word332","word1839","word2626","word2382","word3452","word2631","word2826","word1154","word956","word348","word935","word352","word2825","word2882","word3588","word1439","word3218","word87","word2827","word3581","word2745","word3294","word2465","word1713","word378","word239","word1639","word1696","word1729","word1536","word3247","word478","word1684","word311","word3377","word701","word1279","word391","word2433","word3234","word6","word3548","word2555","word1208","word1537","word503","word849","word907","word1878","word1531","word703","word2834","word1267","word1649","word3240","word18","word3465","word1156","word2073","word2383","word329","word880","word2335","word2351","word3308","word3434","word735","word2627","word1078","word1165","word1810","word1792","word3320","word3630","word912","word1004","word2646","word2945","word1711","word1217","word1113","word1702","word3579","word1224","word1586","word3351","word1592","word1748","word1232","word2262","word1946","word3221","word1095","word327","word1316","word3698","word3011","word1255","word342","word3262","word1993","word1819","word1391","word1525","word2137","word2535","word3461","word441","word80","word153","word2905","word206","word2943","word2630","word570","word3419","word2902","word3415","word1613","word119","word1755","word2464","word1837","word3584","word185","word1674","word3309","word2951","word135","word2848","word3047","word2067","word2647","word1486","word1043","word2338","word3552","word1762","word3124","word724","word474","word721","word1372","word2021","word3616","word2373","word2976","word1736","word2454","word3034","word3400","word1630","word3293","word3381","class_label of content","Agents","IR","ML","AI","DB","HCI","identifier of content","paper_id of paper","class_label of paper","identifier of paper"]
|
|
|
|
|
|
join-arnaud-citeseer/text_emb_all-MiniLM-L12-v2.bin
DELETED
|
@@ -1,3 +0,0 @@
|
|
| 1 |
-
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:26922fc07d48dee718559eb3d7a4fc4dc0c695ed56a27ce0068a302b92f10c77
|
| 3 |
-
size 5412864
|
|
|
|
|
|
|
|
|
|
|
|
join-beeradvocate/column_index.json
DELETED
|
@@ -1 +0,0 @@
|
|
| 1 |
-
{"timestamp of beer-review-existence":74,"timestamp of reviewer-has-review":36,"timestamp of reviewer-harsh-rater":63369,"reviewer_id of reviewer-gives-perfect-rare":19,"max_overall of beer-max-overall":63484,"avg_over_given of reviewer-mean-overall-given":8,"timestamp of beer-sum-review-len":63425,"look_vs_palate of beer-appearance-palate-ratio":32,"reviewer_return of reviewer-return":63501,"will_repeat_long of new-reviewer-repeat-long-cold-start":63505,"timestamp of beer-perfect-appearance-rare":66,"beer_id of beer-rating-trend":63471,"has_perfect_palate of beer-perfect-palate-rare":63377,"beer_id of new-beer-five-window-cold-start":55,"timestamp of beer-total-review-length":17,"predict_reviewer_has_review of reviewer-has-review":37,"distinct_beers of reviewer-distinct-beers":63480,"beer_id of beer-appearance-palate-ratio":31,"five_window_reviewed of new-beer-five-window-cold-start":57,"review_length_change of reviewer-review-length-change":63444,"avg_taste_given of reviewer-mean-taste":63440,"avg_appearance of beer-mean-appearance":63404,"avg_taste of beer-mean-taste":52,"timestamp of reviewer-mean-overall-given":9,"timestamp of beer-mean-taste":53,"review_len of reviews":63365,"reviewer_id of reviewer-mean-taste":63439,"taste of reviews":63363,"top_rated_beer of beer-top-rated":3,"reviewer_id of reviewer-has-review":35,"tight_active of new-reviewer-tight-cold-start":63397,"timestamp of new-beer-three-window-cold-start":48,"identifier of reviewers":63,"timestamp of beer-high-rating":41,"beer_id of beer-review-return":63415,"timestamp of reviewer-review-length":63433,"timestamp of reviewer-mean-taste":63441,"timestamp of beer-review-count":63457,"three_window_active of new-reviewer-three-window-cold-start":63461,"reviewer_id of new-reviewer-tight-cold-start":63395,"timestamp of beer-max-overall":63485,"timestamp of reviewer-mean-overall":63453,"avg_reviewer_rating of reviewer-mean-overall":63452,"timestamp of beer-min-overall":63469,"has_epic_review of beer-epic-review-rare":63393,"overall of reviews":63359,"predict_beer_churn of beer-churn":13,"avg_palate of beer-mean-palate":63346,"beer_id of beer-perfect-overall-rare":23,"timestamp of new-beer-repeat-cold-start":70,"reviewer_id of reviewer-review-length-change":63443,"reviewer_id of reviewer-return":63499,"mean_review_len of beer-avg-review-length":60,"highly_rated of beer-highly-rated":63342,"viral_burst of beer-viral-burst-rare":63389,"timestamp of beer-aroma-to-taste-ratio":63489,"timestamp of beer-rating-change":63493,"timestamp of reviewer-return":63500,"long_reviews of reviewer-extended-count":63508,"top_active_reviewer of reviewer-top-active":63512,"style of beers":56938,"will_repeat of new-reviewer-repeat-cold-start":63351,"timestamp of new-beer-tight-cold-start":63496,"avg_overall of beer-mean-overall":63372,"beer_id of beer-mean-taste":51,"aroma of reviews":63360,"tight_reviewed of new-beer-tight-cold-start":63497,"beer_id of beer-perfect-aroma-rare":43,"reviewer_id of reviewer-sum-review-len":27,"total_words of reviewer-sum-review-len":28,"timestamp of reviewer-churn":78,"timestamp of beer-churn":12,"has_perfect_overall of beer-perfect-overall-rare":25,"timestamp of reviewer-sum-review-len":29,"timestamp of beer-mean-palate":63347,"timestamp of beer-overall-to-taste-ratio":63385,"timestamp of reviewer-gives-perfect-rare":20,"predict_reviewer_review_count of reviewer-review-count":63400,"total_text_length of beer-total-review-length":16,"rating_volatility of beer-rating-volatility":63428,"timestamp of reviewer-long-review":63413,"beer_id of beer-high-rating":39,"beer_id of new-beer-repeat-cold-start":69,"timestamp of reviewer-review-count":63401,"reviewer_id of new-reviewer-three-window-cold-start":63459,"beer_id of beer-aroma-to-taste-ratio":63487,"reviewer_id of reviewer-harsh-rater":63367,"timestamp of new-reviewer-repeat-long-cold-start":63504,"timestamp of new-reviewer-three-window-cold-start":63460,"beer_id of beer-max-overall":63483,"timestamp of reviewer-writes-epic-rare":63516,"has_perfect_appearance of beer-perfect-appearance-rare":67,"reviewer_id of reviews":63357,"reviewer_id of reviewer-review-existence":63353,"timestamp of reviews":63364,"beer_id of beer-mean-aroma":63379,"harsh_reviewer of reviewer-harsh-review":63448,"will_repeat_long of new-beer-repeat-long-cold-start":63477,"beer_id of beer-mean-overall":63371,"reviewer_id of reviewer-top-active":63511,"beer_id of new-beer-tight-cold-start":63495,"beer_id of beer-avg-review-length":59,"reviewer_id of reviewer-writes-epic-rare":63515,"reviewer_id of reviewer-mean-overall":63451,"timestamp of new-beer-five-window-cold-start":56,"reviewer_id of reviewers":62,"beer_id of beer-churn":11,"name of beers":81,"beer_id of beer-mean-palate":63345,"beer_id of beer-overall-to-taste-ratio":63383,"brewer_id of beers":57518,"timestamp of beer-highly-rated":63343,"timestamp of new-reviewer-five-window-cold-start":63436,"predict_reviewer_churn of reviewer-churn":79,"avg_aroma of beer-mean-aroma":63380,"o_t_ratio of beer-overall-to-taste-ratio":63384,"rating_trend of beer-rating-trend":63472,"reviewer_id of new-reviewer-repeat-long-cold-start":63503,"beer_id of beer-highly-rated":63341,"beer_id of beer-top-rated":1,"gives_perfect_score of reviewer-gives-perfect-rare":21,"reviewer_id of reviewer-churn":77,"beer_id of reviews":63358,"timestamp of beer-perfect-aroma-rare":44,"beer_id of beer-perfect-taste-rare":63419,"reviewer_id of new-reviewer-repeat-cold-start":63349,"beer_id of beer-epic-review-rare":63391,"reviewer_id of reviewer-review-length":63431,"beer_id of beer-rating-volatility":63427,"timestamp of reviewer-harsh-review":63449,"has_perfect_taste of beer-perfect-taste-rare":63421,"timestamp of reviewer-gives-zero-rare":63464,"timestamp of beer-rating-trend":63473,"reviewer_id of reviewer-distinct-beers":63479,"timestamp of beer-perfect-taste-rare":63420,"reviewer_id of reviewer-extended-count":63507,"beer_id of beer-review-concentration":63337,"timestamp of reviewer-extended-count":63509,"writes_epic_review of reviewer-writes-epic-rare":63517,"timestamp of beer-appearance-palate-ratio":33,"timestamp of beer-top-rated":4,"beer_id of beer-perfect-palate-rare":63375,"beer_review_return of beer-review-return":63417,"beer_id of new-beer-three-window-cold-start":47,"timestamp of reviewer-review-existence":63354,"timestamp of beer-viral-burst-rare":63388,"bad_rated of beer-low-rating":63408,"timestamp of beer-avg-review-length":61,"timestamp of beer-perfect-palate-rare":63376,"gives_zero_overall of reviewer-gives-zero-rare":63465,"timestamp of beer-mean-appearance":63405,"beer_id of beer-mean-appearance":63403,"timestamp of beer-review-concentration":63339,"has_review_next of beer-review-existence":75,"timestamp of beer-low-rating":63409,"reviewer_id of reviewer-long-review":63411,"beer_id of beer-min-overall":63467,"beer_id of beer-total-review-length":15,"rating_change of beer-rating-change":63492,"has_review_next of reviewer-review-existence":63355,"timestamp of beer-mean-aroma":63381,"timestamp of new-reviewer-tight-cold-start":63396,"beer_id of new-beer-repeat-long-cold-start":63475,"timestamp of beer-rating-volatility":63429,"timestamp of beer-mean-overall":63373,"review_concentration of beer-review-concentration":63338,"reviewer_id of reviewer-review-count":63399,"writes_long of reviewer-long-review":63412,"reviewer_id of new-reviewer-five-window-cold-start":63435,"timestamp of reviewer-review-length-change":63445,"reviewer_id of reviewer-mean-overall-given":6,"timestamp of beer-review-return":63416,"timestamp of beer-epic-review-rare":63392,"predict_beer_review_count of beer-review-count":63456,"timestamp of new-beer-repeat-long-cold-start":63476,"timestamp of reviewer-top-active":63513,"beer_id of beers":80,"high_rated of beer-high-rating":40,"has_perfect_aroma of beer-perfect-aroma-rare":45,"beer_id of beer-sum-review-len":63423,"min_overall of beer-min-overall":63468,"abv of beers":56986,"harsh_reviewer of reviewer-harsh-rater":63368,"beer_id of beer-perfect-appearance-rare":65,"timestamp of beer-perfect-overall-rare":24,"beer_id of beer-viral-burst-rare":63387,"palate of reviews":63362,"five_window_active of new-reviewer-five-window-cold-start":63437,"reviewer_id of reviewer-harsh-review":63447,"beer_id of beer-review-count":63455,"total_review_len of beer-sum-review-len":63424,"aroma_taste_ratio of beer-aroma-to-taste-ratio":63488,"beer_id of beer-rating-change":63491,"timestamp of new-reviewer-repeat-cold-start":63350,"timestamp of reviewer-distinct-beers":63481,"appearance of reviews":63361,"beer_id of beer-low-rating":63407,"reviewer_id of reviewer-gives-zero-rare":63463,"will_repeat of new-beer-repeat-cold-start":71,"beer_id of beer-review-existence":73,"pred_review_len of reviewer-review-length":63432,"three_window_reviewed of new-beer-three-window-cold-start":49}
|
|
|
|
|
|
join-beeradvocate/meta.json
DELETED
|
@@ -1,761 +0,0 @@
|
|
| 1 |
-
{
|
| 2 |
-
"files": {
|
| 3 |
-
"column_index": "column_index.json",
|
| 4 |
-
"nodes": "nodes.rkyv",
|
| 5 |
-
"offsets": "offsets.rkyv",
|
| 6 |
-
"p2f_adj": "p2f_adj.rkyv",
|
| 7 |
-
"table_info": "table_info.json",
|
| 8 |
-
"text": "text.json"
|
| 9 |
-
},
|
| 10 |
-
"format_version": 1,
|
| 11 |
-
"name": "join-beeradvocate",
|
| 12 |
-
"num_db_tables": 3,
|
| 13 |
-
"num_nodes": 17335264,
|
| 14 |
-
"num_task_tables": 62,
|
| 15 |
-
"num_text_strings": 63518,
|
| 16 |
-
"source": "stanford-star/the-join/join-beeradvocate",
|
| 17 |
-
"tasks": [
|
| 18 |
-
{
|
| 19 |
-
"entity_table": "beers",
|
| 20 |
-
"kind": "forecast",
|
| 21 |
-
"name": "beer-appearance-palate-ratio",
|
| 22 |
-
"splits": [
|
| 23 |
-
"train"
|
| 24 |
-
],
|
| 25 |
-
"target_col": "look_vs_palate",
|
| 26 |
-
"task_type": "regression",
|
| 27 |
-
"time_col": "timestamp"
|
| 28 |
-
},
|
| 29 |
-
{
|
| 30 |
-
"entity_table": "beers",
|
| 31 |
-
"kind": "forecast",
|
| 32 |
-
"name": "beer-aroma-to-taste-ratio",
|
| 33 |
-
"splits": [
|
| 34 |
-
"train"
|
| 35 |
-
],
|
| 36 |
-
"target_col": "aroma_taste_ratio",
|
| 37 |
-
"task_type": "regression",
|
| 38 |
-
"time_col": "timestamp"
|
| 39 |
-
},
|
| 40 |
-
{
|
| 41 |
-
"entity_table": "beers",
|
| 42 |
-
"kind": "forecast",
|
| 43 |
-
"name": "beer-avg-review-length",
|
| 44 |
-
"splits": [
|
| 45 |
-
"train"
|
| 46 |
-
],
|
| 47 |
-
"target_col": "mean_review_len",
|
| 48 |
-
"task_type": "regression",
|
| 49 |
-
"time_col": "timestamp"
|
| 50 |
-
},
|
| 51 |
-
{
|
| 52 |
-
"entity_table": "beers",
|
| 53 |
-
"kind": "forecast",
|
| 54 |
-
"name": "beer-churn",
|
| 55 |
-
"splits": [
|
| 56 |
-
"train"
|
| 57 |
-
],
|
| 58 |
-
"target_col": "predict_beer_churn",
|
| 59 |
-
"task_type": "binary_classification",
|
| 60 |
-
"time_col": "timestamp"
|
| 61 |
-
},
|
| 62 |
-
{
|
| 63 |
-
"entity_table": "beers",
|
| 64 |
-
"kind": "forecast",
|
| 65 |
-
"name": "beer-epic-review-rare",
|
| 66 |
-
"splits": [
|
| 67 |
-
"train"
|
| 68 |
-
],
|
| 69 |
-
"target_col": "has_epic_review",
|
| 70 |
-
"task_type": "binary_classification",
|
| 71 |
-
"time_col": "timestamp"
|
| 72 |
-
},
|
| 73 |
-
{
|
| 74 |
-
"entity_table": "beers",
|
| 75 |
-
"kind": "forecast",
|
| 76 |
-
"name": "beer-high-rating",
|
| 77 |
-
"splits": [
|
| 78 |
-
"train"
|
| 79 |
-
],
|
| 80 |
-
"target_col": "high_rated",
|
| 81 |
-
"task_type": "binary_classification",
|
| 82 |
-
"time_col": "timestamp"
|
| 83 |
-
},
|
| 84 |
-
{
|
| 85 |
-
"entity_table": "beers",
|
| 86 |
-
"kind": "forecast",
|
| 87 |
-
"name": "beer-highly-rated",
|
| 88 |
-
"splits": [
|
| 89 |
-
"train"
|
| 90 |
-
],
|
| 91 |
-
"target_col": "highly_rated",
|
| 92 |
-
"task_type": "binary_classification",
|
| 93 |
-
"time_col": "timestamp"
|
| 94 |
-
},
|
| 95 |
-
{
|
| 96 |
-
"entity_table": "beers",
|
| 97 |
-
"kind": "forecast",
|
| 98 |
-
"name": "beer-low-rating",
|
| 99 |
-
"splits": [
|
| 100 |
-
"train"
|
| 101 |
-
],
|
| 102 |
-
"target_col": "bad_rated",
|
| 103 |
-
"task_type": "binary_classification",
|
| 104 |
-
"time_col": "timestamp"
|
| 105 |
-
},
|
| 106 |
-
{
|
| 107 |
-
"entity_table": "beers",
|
| 108 |
-
"kind": "forecast",
|
| 109 |
-
"name": "beer-max-overall",
|
| 110 |
-
"splits": [
|
| 111 |
-
"train"
|
| 112 |
-
],
|
| 113 |
-
"target_col": "max_overall",
|
| 114 |
-
"task_type": "regression",
|
| 115 |
-
"time_col": "timestamp"
|
| 116 |
-
},
|
| 117 |
-
{
|
| 118 |
-
"entity_table": "beers",
|
| 119 |
-
"kind": "forecast",
|
| 120 |
-
"name": "beer-mean-appearance",
|
| 121 |
-
"splits": [
|
| 122 |
-
"train"
|
| 123 |
-
],
|
| 124 |
-
"target_col": "avg_appearance",
|
| 125 |
-
"task_type": "regression",
|
| 126 |
-
"time_col": "timestamp"
|
| 127 |
-
},
|
| 128 |
-
{
|
| 129 |
-
"entity_table": "beers",
|
| 130 |
-
"kind": "forecast",
|
| 131 |
-
"name": "beer-mean-aroma",
|
| 132 |
-
"splits": [
|
| 133 |
-
"train"
|
| 134 |
-
],
|
| 135 |
-
"target_col": "avg_aroma",
|
| 136 |
-
"task_type": "regression",
|
| 137 |
-
"time_col": "timestamp"
|
| 138 |
-
},
|
| 139 |
-
{
|
| 140 |
-
"entity_table": "beers",
|
| 141 |
-
"kind": "forecast",
|
| 142 |
-
"name": "beer-mean-overall",
|
| 143 |
-
"splits": [
|
| 144 |
-
"train"
|
| 145 |
-
],
|
| 146 |
-
"target_col": "avg_overall",
|
| 147 |
-
"task_type": "regression",
|
| 148 |
-
"time_col": "timestamp"
|
| 149 |
-
},
|
| 150 |
-
{
|
| 151 |
-
"entity_table": "beers",
|
| 152 |
-
"kind": "forecast",
|
| 153 |
-
"name": "beer-mean-palate",
|
| 154 |
-
"splits": [
|
| 155 |
-
"train"
|
| 156 |
-
],
|
| 157 |
-
"target_col": "avg_palate",
|
| 158 |
-
"task_type": "regression",
|
| 159 |
-
"time_col": "timestamp"
|
| 160 |
-
},
|
| 161 |
-
{
|
| 162 |
-
"entity_table": "beers",
|
| 163 |
-
"kind": "forecast",
|
| 164 |
-
"name": "beer-mean-taste",
|
| 165 |
-
"splits": [
|
| 166 |
-
"train"
|
| 167 |
-
],
|
| 168 |
-
"target_col": "avg_taste",
|
| 169 |
-
"task_type": "regression",
|
| 170 |
-
"time_col": "timestamp"
|
| 171 |
-
},
|
| 172 |
-
{
|
| 173 |
-
"entity_table": "beers",
|
| 174 |
-
"kind": "forecast",
|
| 175 |
-
"name": "beer-min-overall",
|
| 176 |
-
"splits": [
|
| 177 |
-
"train"
|
| 178 |
-
],
|
| 179 |
-
"target_col": "min_overall",
|
| 180 |
-
"task_type": "regression",
|
| 181 |
-
"time_col": "timestamp"
|
| 182 |
-
},
|
| 183 |
-
{
|
| 184 |
-
"entity_table": "beers",
|
| 185 |
-
"kind": "forecast",
|
| 186 |
-
"name": "beer-overall-to-taste-ratio",
|
| 187 |
-
"splits": [
|
| 188 |
-
"train"
|
| 189 |
-
],
|
| 190 |
-
"target_col": "o_t_ratio",
|
| 191 |
-
"task_type": "regression",
|
| 192 |
-
"time_col": "timestamp"
|
| 193 |
-
},
|
| 194 |
-
{
|
| 195 |
-
"entity_table": "beers",
|
| 196 |
-
"kind": "forecast",
|
| 197 |
-
"name": "beer-perfect-appearance-rare",
|
| 198 |
-
"splits": [
|
| 199 |
-
"train"
|
| 200 |
-
],
|
| 201 |
-
"target_col": "has_perfect_appearance",
|
| 202 |
-
"task_type": "binary_classification",
|
| 203 |
-
"time_col": "timestamp"
|
| 204 |
-
},
|
| 205 |
-
{
|
| 206 |
-
"entity_table": "beers",
|
| 207 |
-
"kind": "forecast",
|
| 208 |
-
"name": "beer-perfect-aroma-rare",
|
| 209 |
-
"splits": [
|
| 210 |
-
"train"
|
| 211 |
-
],
|
| 212 |
-
"target_col": "has_perfect_aroma",
|
| 213 |
-
"task_type": "binary_classification",
|
| 214 |
-
"time_col": "timestamp"
|
| 215 |
-
},
|
| 216 |
-
{
|
| 217 |
-
"entity_table": "beers",
|
| 218 |
-
"kind": "forecast",
|
| 219 |
-
"name": "beer-perfect-overall-rare",
|
| 220 |
-
"splits": [
|
| 221 |
-
"train"
|
| 222 |
-
],
|
| 223 |
-
"target_col": "has_perfect_overall",
|
| 224 |
-
"task_type": "binary_classification",
|
| 225 |
-
"time_col": "timestamp"
|
| 226 |
-
},
|
| 227 |
-
{
|
| 228 |
-
"entity_table": "beers",
|
| 229 |
-
"kind": "forecast",
|
| 230 |
-
"name": "beer-perfect-palate-rare",
|
| 231 |
-
"splits": [
|
| 232 |
-
"train"
|
| 233 |
-
],
|
| 234 |
-
"target_col": "has_perfect_palate",
|
| 235 |
-
"task_type": "binary_classification",
|
| 236 |
-
"time_col": "timestamp"
|
| 237 |
-
},
|
| 238 |
-
{
|
| 239 |
-
"entity_table": "beers",
|
| 240 |
-
"kind": "forecast",
|
| 241 |
-
"name": "beer-perfect-taste-rare",
|
| 242 |
-
"splits": [
|
| 243 |
-
"train"
|
| 244 |
-
],
|
| 245 |
-
"target_col": "has_perfect_taste",
|
| 246 |
-
"task_type": "binary_classification",
|
| 247 |
-
"time_col": "timestamp"
|
| 248 |
-
},
|
| 249 |
-
{
|
| 250 |
-
"entity_table": "beers",
|
| 251 |
-
"kind": "forecast",
|
| 252 |
-
"name": "beer-rating-change",
|
| 253 |
-
"splits": [
|
| 254 |
-
"train"
|
| 255 |
-
],
|
| 256 |
-
"target_col": "rating_change",
|
| 257 |
-
"task_type": "regression",
|
| 258 |
-
"time_col": "timestamp"
|
| 259 |
-
},
|
| 260 |
-
{
|
| 261 |
-
"entity_table": "beers",
|
| 262 |
-
"kind": "forecast",
|
| 263 |
-
"name": "beer-rating-trend",
|
| 264 |
-
"splits": [
|
| 265 |
-
"train"
|
| 266 |
-
],
|
| 267 |
-
"target_col": "rating_trend",
|
| 268 |
-
"task_type": "binary_classification",
|
| 269 |
-
"time_col": "timestamp"
|
| 270 |
-
},
|
| 271 |
-
{
|
| 272 |
-
"entity_table": "beers",
|
| 273 |
-
"kind": "forecast",
|
| 274 |
-
"name": "beer-rating-volatility",
|
| 275 |
-
"splits": [
|
| 276 |
-
"train"
|
| 277 |
-
],
|
| 278 |
-
"target_col": "rating_volatility",
|
| 279 |
-
"task_type": "regression",
|
| 280 |
-
"time_col": "timestamp"
|
| 281 |
-
},
|
| 282 |
-
{
|
| 283 |
-
"entity_table": "beers",
|
| 284 |
-
"kind": "forecast",
|
| 285 |
-
"name": "beer-review-concentration",
|
| 286 |
-
"splits": [
|
| 287 |
-
"train"
|
| 288 |
-
],
|
| 289 |
-
"target_col": "review_concentration",
|
| 290 |
-
"task_type": "regression",
|
| 291 |
-
"time_col": "timestamp"
|
| 292 |
-
},
|
| 293 |
-
{
|
| 294 |
-
"entity_table": "beers",
|
| 295 |
-
"kind": "forecast",
|
| 296 |
-
"name": "beer-review-count",
|
| 297 |
-
"splits": [
|
| 298 |
-
"train"
|
| 299 |
-
],
|
| 300 |
-
"target_col": "predict_beer_review_count",
|
| 301 |
-
"task_type": "regression",
|
| 302 |
-
"time_col": "timestamp"
|
| 303 |
-
},
|
| 304 |
-
{
|
| 305 |
-
"entity_table": "beers",
|
| 306 |
-
"kind": "forecast",
|
| 307 |
-
"name": "beer-review-existence",
|
| 308 |
-
"splits": [
|
| 309 |
-
"train"
|
| 310 |
-
],
|
| 311 |
-
"target_col": "has_review_next",
|
| 312 |
-
"task_type": "binary_classification",
|
| 313 |
-
"time_col": "timestamp"
|
| 314 |
-
},
|
| 315 |
-
{
|
| 316 |
-
"entity_table": "beers",
|
| 317 |
-
"kind": "forecast",
|
| 318 |
-
"name": "beer-review-return",
|
| 319 |
-
"splits": [
|
| 320 |
-
"train"
|
| 321 |
-
],
|
| 322 |
-
"target_col": "beer_review_return",
|
| 323 |
-
"task_type": "binary_classification",
|
| 324 |
-
"time_col": "timestamp"
|
| 325 |
-
},
|
| 326 |
-
{
|
| 327 |
-
"entity_table": "beers",
|
| 328 |
-
"kind": "forecast",
|
| 329 |
-
"name": "beer-sum-review-len",
|
| 330 |
-
"splits": [
|
| 331 |
-
"train"
|
| 332 |
-
],
|
| 333 |
-
"target_col": "total_review_len",
|
| 334 |
-
"task_type": "regression",
|
| 335 |
-
"time_col": "timestamp"
|
| 336 |
-
},
|
| 337 |
-
{
|
| 338 |
-
"entity_table": "beers",
|
| 339 |
-
"kind": "forecast",
|
| 340 |
-
"name": "beer-top-rated",
|
| 341 |
-
"splits": [
|
| 342 |
-
"train"
|
| 343 |
-
],
|
| 344 |
-
"target_col": "top_rated_beer",
|
| 345 |
-
"task_type": "binary_classification",
|
| 346 |
-
"time_col": "timestamp"
|
| 347 |
-
},
|
| 348 |
-
{
|
| 349 |
-
"entity_table": "beers",
|
| 350 |
-
"kind": "forecast",
|
| 351 |
-
"name": "beer-total-review-length",
|
| 352 |
-
"splits": [
|
| 353 |
-
"train"
|
| 354 |
-
],
|
| 355 |
-
"target_col": "total_text_length",
|
| 356 |
-
"task_type": "regression",
|
| 357 |
-
"time_col": "timestamp"
|
| 358 |
-
},
|
| 359 |
-
{
|
| 360 |
-
"entity_table": "beers",
|
| 361 |
-
"kind": "forecast",
|
| 362 |
-
"name": "beer-viral-burst-rare",
|
| 363 |
-
"splits": [
|
| 364 |
-
"train"
|
| 365 |
-
],
|
| 366 |
-
"target_col": "viral_burst",
|
| 367 |
-
"task_type": "binary_classification",
|
| 368 |
-
"time_col": "timestamp"
|
| 369 |
-
},
|
| 370 |
-
{
|
| 371 |
-
"entity_table": "beers",
|
| 372 |
-
"kind": "forecast",
|
| 373 |
-
"name": "new-beer-five-window-cold-start",
|
| 374 |
-
"splits": [
|
| 375 |
-
"train"
|
| 376 |
-
],
|
| 377 |
-
"target_col": "five_window_reviewed",
|
| 378 |
-
"task_type": "binary_classification",
|
| 379 |
-
"time_col": "timestamp"
|
| 380 |
-
},
|
| 381 |
-
{
|
| 382 |
-
"entity_table": "beers",
|
| 383 |
-
"kind": "forecast",
|
| 384 |
-
"name": "new-beer-repeat-cold-start",
|
| 385 |
-
"splits": [
|
| 386 |
-
"train"
|
| 387 |
-
],
|
| 388 |
-
"target_col": "will_repeat",
|
| 389 |
-
"task_type": "binary_classification",
|
| 390 |
-
"time_col": "timestamp"
|
| 391 |
-
},
|
| 392 |
-
{
|
| 393 |
-
"entity_table": "beers",
|
| 394 |
-
"kind": "forecast",
|
| 395 |
-
"name": "new-beer-repeat-long-cold-start",
|
| 396 |
-
"splits": [
|
| 397 |
-
"train"
|
| 398 |
-
],
|
| 399 |
-
"target_col": "will_repeat_long",
|
| 400 |
-
"task_type": "binary_classification",
|
| 401 |
-
"time_col": "timestamp"
|
| 402 |
-
},
|
| 403 |
-
{
|
| 404 |
-
"entity_table": "beers",
|
| 405 |
-
"kind": "forecast",
|
| 406 |
-
"name": "new-beer-three-window-cold-start",
|
| 407 |
-
"splits": [
|
| 408 |
-
"train"
|
| 409 |
-
],
|
| 410 |
-
"target_col": "three_window_reviewed",
|
| 411 |
-
"task_type": "binary_classification",
|
| 412 |
-
"time_col": "timestamp"
|
| 413 |
-
},
|
| 414 |
-
{
|
| 415 |
-
"entity_table": "beers",
|
| 416 |
-
"kind": "forecast",
|
| 417 |
-
"name": "new-beer-tight-cold-start",
|
| 418 |
-
"splits": [
|
| 419 |
-
"train"
|
| 420 |
-
],
|
| 421 |
-
"target_col": "tight_reviewed",
|
| 422 |
-
"task_type": "binary_classification",
|
| 423 |
-
"time_col": "timestamp"
|
| 424 |
-
},
|
| 425 |
-
{
|
| 426 |
-
"entity_table": "reviewers",
|
| 427 |
-
"kind": "forecast",
|
| 428 |
-
"name": "new-reviewer-five-window-cold-start",
|
| 429 |
-
"splits": [
|
| 430 |
-
"train"
|
| 431 |
-
],
|
| 432 |
-
"target_col": "five_window_active",
|
| 433 |
-
"task_type": "binary_classification",
|
| 434 |
-
"time_col": "timestamp"
|
| 435 |
-
},
|
| 436 |
-
{
|
| 437 |
-
"entity_table": "reviewers",
|
| 438 |
-
"kind": "forecast",
|
| 439 |
-
"name": "new-reviewer-repeat-cold-start",
|
| 440 |
-
"splits": [
|
| 441 |
-
"train"
|
| 442 |
-
],
|
| 443 |
-
"target_col": "will_repeat",
|
| 444 |
-
"task_type": "binary_classification",
|
| 445 |
-
"time_col": "timestamp"
|
| 446 |
-
},
|
| 447 |
-
{
|
| 448 |
-
"entity_table": "reviewers",
|
| 449 |
-
"kind": "forecast",
|
| 450 |
-
"name": "new-reviewer-repeat-long-cold-start",
|
| 451 |
-
"splits": [
|
| 452 |
-
"train"
|
| 453 |
-
],
|
| 454 |
-
"target_col": "will_repeat_long",
|
| 455 |
-
"task_type": "binary_classification",
|
| 456 |
-
"time_col": "timestamp"
|
| 457 |
-
},
|
| 458 |
-
{
|
| 459 |
-
"entity_table": "reviewers",
|
| 460 |
-
"kind": "forecast",
|
| 461 |
-
"name": "new-reviewer-three-window-cold-start",
|
| 462 |
-
"splits": [
|
| 463 |
-
"train"
|
| 464 |
-
],
|
| 465 |
-
"target_col": "three_window_active",
|
| 466 |
-
"task_type": "binary_classification",
|
| 467 |
-
"time_col": "timestamp"
|
| 468 |
-
},
|
| 469 |
-
{
|
| 470 |
-
"entity_table": "reviewers",
|
| 471 |
-
"kind": "forecast",
|
| 472 |
-
"name": "new-reviewer-tight-cold-start",
|
| 473 |
-
"splits": [
|
| 474 |
-
"train"
|
| 475 |
-
],
|
| 476 |
-
"target_col": "tight_active",
|
| 477 |
-
"task_type": "binary_classification",
|
| 478 |
-
"time_col": "timestamp"
|
| 479 |
-
},
|
| 480 |
-
{
|
| 481 |
-
"entity_table": "reviewers",
|
| 482 |
-
"kind": "forecast",
|
| 483 |
-
"name": "reviewer-churn",
|
| 484 |
-
"splits": [
|
| 485 |
-
"train"
|
| 486 |
-
],
|
| 487 |
-
"target_col": "predict_reviewer_churn",
|
| 488 |
-
"task_type": "binary_classification",
|
| 489 |
-
"time_col": "timestamp"
|
| 490 |
-
},
|
| 491 |
-
{
|
| 492 |
-
"entity_table": "reviewers",
|
| 493 |
-
"kind": "forecast",
|
| 494 |
-
"name": "reviewer-distinct-beers",
|
| 495 |
-
"splits": [
|
| 496 |
-
"train"
|
| 497 |
-
],
|
| 498 |
-
"target_col": "distinct_beers",
|
| 499 |
-
"task_type": "regression",
|
| 500 |
-
"time_col": "timestamp"
|
| 501 |
-
},
|
| 502 |
-
{
|
| 503 |
-
"entity_table": "reviewers",
|
| 504 |
-
"kind": "forecast",
|
| 505 |
-
"name": "reviewer-extended-count",
|
| 506 |
-
"splits": [
|
| 507 |
-
"train"
|
| 508 |
-
],
|
| 509 |
-
"target_col": "long_reviews",
|
| 510 |
-
"task_type": "regression",
|
| 511 |
-
"time_col": "timestamp"
|
| 512 |
-
},
|
| 513 |
-
{
|
| 514 |
-
"entity_table": "reviewers",
|
| 515 |
-
"kind": "forecast",
|
| 516 |
-
"name": "reviewer-gives-perfect-rare",
|
| 517 |
-
"splits": [
|
| 518 |
-
"train"
|
| 519 |
-
],
|
| 520 |
-
"target_col": "gives_perfect_score",
|
| 521 |
-
"task_type": "binary_classification",
|
| 522 |
-
"time_col": "timestamp"
|
| 523 |
-
},
|
| 524 |
-
{
|
| 525 |
-
"entity_table": "reviewers",
|
| 526 |
-
"kind": "forecast",
|
| 527 |
-
"name": "reviewer-gives-zero-rare",
|
| 528 |
-
"splits": [
|
| 529 |
-
"train"
|
| 530 |
-
],
|
| 531 |
-
"target_col": "gives_zero_overall",
|
| 532 |
-
"task_type": "binary_classification",
|
| 533 |
-
"time_col": "timestamp"
|
| 534 |
-
},
|
| 535 |
-
{
|
| 536 |
-
"entity_table": "reviewers",
|
| 537 |
-
"kind": "forecast",
|
| 538 |
-
"name": "reviewer-harsh-rater",
|
| 539 |
-
"splits": [
|
| 540 |
-
"train"
|
| 541 |
-
],
|
| 542 |
-
"target_col": "harsh_reviewer",
|
| 543 |
-
"task_type": "binary_classification",
|
| 544 |
-
"time_col": "timestamp"
|
| 545 |
-
},
|
| 546 |
-
{
|
| 547 |
-
"entity_table": "reviewers",
|
| 548 |
-
"kind": "forecast",
|
| 549 |
-
"name": "reviewer-harsh-review",
|
| 550 |
-
"splits": [
|
| 551 |
-
"train"
|
| 552 |
-
],
|
| 553 |
-
"target_col": "harsh_reviewer",
|
| 554 |
-
"task_type": "binary_classification",
|
| 555 |
-
"time_col": "timestamp"
|
| 556 |
-
},
|
| 557 |
-
{
|
| 558 |
-
"entity_table": "reviewers",
|
| 559 |
-
"kind": "forecast",
|
| 560 |
-
"name": "reviewer-has-review",
|
| 561 |
-
"splits": [
|
| 562 |
-
"train"
|
| 563 |
-
],
|
| 564 |
-
"target_col": "predict_reviewer_has_review",
|
| 565 |
-
"task_type": "binary_classification",
|
| 566 |
-
"time_col": "timestamp"
|
| 567 |
-
},
|
| 568 |
-
{
|
| 569 |
-
"entity_table": "reviewers",
|
| 570 |
-
"kind": "forecast",
|
| 571 |
-
"name": "reviewer-long-review",
|
| 572 |
-
"splits": [
|
| 573 |
-
"train"
|
| 574 |
-
],
|
| 575 |
-
"target_col": "writes_long",
|
| 576 |
-
"task_type": "binary_classification",
|
| 577 |
-
"time_col": "timestamp"
|
| 578 |
-
},
|
| 579 |
-
{
|
| 580 |
-
"entity_table": "reviewers",
|
| 581 |
-
"kind": "forecast",
|
| 582 |
-
"name": "reviewer-mean-overall",
|
| 583 |
-
"splits": [
|
| 584 |
-
"train"
|
| 585 |
-
],
|
| 586 |
-
"target_col": "avg_reviewer_rating",
|
| 587 |
-
"task_type": "regression",
|
| 588 |
-
"time_col": "timestamp"
|
| 589 |
-
},
|
| 590 |
-
{
|
| 591 |
-
"entity_table": "reviewers",
|
| 592 |
-
"kind": "forecast",
|
| 593 |
-
"name": "reviewer-mean-overall-given",
|
| 594 |
-
"splits": [
|
| 595 |
-
"train"
|
| 596 |
-
],
|
| 597 |
-
"target_col": "avg_over_given",
|
| 598 |
-
"task_type": "regression",
|
| 599 |
-
"time_col": "timestamp"
|
| 600 |
-
},
|
| 601 |
-
{
|
| 602 |
-
"entity_table": "reviewers",
|
| 603 |
-
"kind": "forecast",
|
| 604 |
-
"name": "reviewer-mean-taste",
|
| 605 |
-
"splits": [
|
| 606 |
-
"train"
|
| 607 |
-
],
|
| 608 |
-
"target_col": "avg_taste_given",
|
| 609 |
-
"task_type": "regression",
|
| 610 |
-
"time_col": "timestamp"
|
| 611 |
-
},
|
| 612 |
-
{
|
| 613 |
-
"entity_table": "reviewers",
|
| 614 |
-
"kind": "forecast",
|
| 615 |
-
"name": "reviewer-return",
|
| 616 |
-
"splits": [
|
| 617 |
-
"train"
|
| 618 |
-
],
|
| 619 |
-
"target_col": "reviewer_return",
|
| 620 |
-
"task_type": "binary_classification",
|
| 621 |
-
"time_col": "timestamp"
|
| 622 |
-
},
|
| 623 |
-
{
|
| 624 |
-
"entity_table": "reviewers",
|
| 625 |
-
"kind": "forecast",
|
| 626 |
-
"name": "reviewer-review-count",
|
| 627 |
-
"splits": [
|
| 628 |
-
"train"
|
| 629 |
-
],
|
| 630 |
-
"target_col": "predict_reviewer_review_count",
|
| 631 |
-
"task_type": "regression",
|
| 632 |
-
"time_col": "timestamp"
|
| 633 |
-
},
|
| 634 |
-
{
|
| 635 |
-
"entity_table": "reviewers",
|
| 636 |
-
"kind": "forecast",
|
| 637 |
-
"name": "reviewer-review-existence",
|
| 638 |
-
"splits": [
|
| 639 |
-
"train"
|
| 640 |
-
],
|
| 641 |
-
"target_col": "has_review_next",
|
| 642 |
-
"task_type": "binary_classification",
|
| 643 |
-
"time_col": "timestamp"
|
| 644 |
-
},
|
| 645 |
-
{
|
| 646 |
-
"entity_table": "reviewers",
|
| 647 |
-
"kind": "forecast",
|
| 648 |
-
"name": "reviewer-review-length",
|
| 649 |
-
"splits": [
|
| 650 |
-
"train"
|
| 651 |
-
],
|
| 652 |
-
"target_col": "pred_review_len",
|
| 653 |
-
"task_type": "regression",
|
| 654 |
-
"time_col": "timestamp"
|
| 655 |
-
},
|
| 656 |
-
{
|
| 657 |
-
"entity_table": "reviewers",
|
| 658 |
-
"kind": "forecast",
|
| 659 |
-
"name": "reviewer-review-length-change",
|
| 660 |
-
"splits": [
|
| 661 |
-
"train"
|
| 662 |
-
],
|
| 663 |
-
"target_col": "review_length_change",
|
| 664 |
-
"task_type": "regression",
|
| 665 |
-
"time_col": "timestamp"
|
| 666 |
-
},
|
| 667 |
-
{
|
| 668 |
-
"entity_table": "reviewers",
|
| 669 |
-
"kind": "forecast",
|
| 670 |
-
"name": "reviewer-sum-review-len",
|
| 671 |
-
"splits": [
|
| 672 |
-
"train"
|
| 673 |
-
],
|
| 674 |
-
"target_col": "total_words",
|
| 675 |
-
"task_type": "regression",
|
| 676 |
-
"time_col": "timestamp"
|
| 677 |
-
},
|
| 678 |
-
{
|
| 679 |
-
"entity_table": "reviewers",
|
| 680 |
-
"kind": "forecast",
|
| 681 |
-
"name": "reviewer-top-active",
|
| 682 |
-
"splits": [
|
| 683 |
-
"train"
|
| 684 |
-
],
|
| 685 |
-
"target_col": "top_active_reviewer",
|
| 686 |
-
"task_type": "binary_classification",
|
| 687 |
-
"time_col": "timestamp"
|
| 688 |
-
},
|
| 689 |
-
{
|
| 690 |
-
"entity_table": "reviewers",
|
| 691 |
-
"kind": "forecast",
|
| 692 |
-
"name": "reviewer-writes-epic-rare",
|
| 693 |
-
"splits": [
|
| 694 |
-
"train"
|
| 695 |
-
],
|
| 696 |
-
"target_col": "writes_epic_review",
|
| 697 |
-
"task_type": "binary_classification",
|
| 698 |
-
"time_col": "timestamp"
|
| 699 |
-
},
|
| 700 |
-
{
|
| 701 |
-
"entity_table": "reviews",
|
| 702 |
-
"kind": "autocomplete",
|
| 703 |
-
"name": "reviews-appearance",
|
| 704 |
-
"splits": [],
|
| 705 |
-
"target_col": "appearance",
|
| 706 |
-
"task_type": "regression",
|
| 707 |
-
"time_col": null
|
| 708 |
-
},
|
| 709 |
-
{
|
| 710 |
-
"entity_table": "reviews",
|
| 711 |
-
"kind": "autocomplete",
|
| 712 |
-
"name": "reviews-aroma",
|
| 713 |
-
"splits": [],
|
| 714 |
-
"target_col": "aroma",
|
| 715 |
-
"task_type": "regression",
|
| 716 |
-
"time_col": null
|
| 717 |
-
},
|
| 718 |
-
{
|
| 719 |
-
"entity_table": "reviews",
|
| 720 |
-
"kind": "autocomplete",
|
| 721 |
-
"name": "reviews-overall",
|
| 722 |
-
"splits": [],
|
| 723 |
-
"target_col": "overall",
|
| 724 |
-
"task_type": "regression",
|
| 725 |
-
"time_col": null
|
| 726 |
-
},
|
| 727 |
-
{
|
| 728 |
-
"entity_table": "reviews",
|
| 729 |
-
"kind": "autocomplete",
|
| 730 |
-
"name": "reviews-palate",
|
| 731 |
-
"splits": [],
|
| 732 |
-
"target_col": "palate",
|
| 733 |
-
"task_type": "regression",
|
| 734 |
-
"time_col": null
|
| 735 |
-
},
|
| 736 |
-
{
|
| 737 |
-
"entity_table": "reviews",
|
| 738 |
-
"kind": "autocomplete",
|
| 739 |
-
"name": "reviews-review_len",
|
| 740 |
-
"splits": [],
|
| 741 |
-
"target_col": "review_len",
|
| 742 |
-
"task_type": "regression",
|
| 743 |
-
"time_col": null
|
| 744 |
-
},
|
| 745 |
-
{
|
| 746 |
-
"entity_table": "reviews",
|
| 747 |
-
"kind": "autocomplete",
|
| 748 |
-
"name": "reviews-taste",
|
| 749 |
-
"splits": [],
|
| 750 |
-
"target_col": "taste",
|
| 751 |
-
"task_type": "regression",
|
| 752 |
-
"time_col": null
|
| 753 |
-
}
|
| 754 |
-
],
|
| 755 |
-
"text_embeddings": {
|
| 756 |
-
"all-MiniLM-L12-v2": {
|
| 757 |
-
"file": "text_emb_all-MiniLM-L12-v2.bin",
|
| 758 |
-
"d_text": 384
|
| 759 |
-
}
|
| 760 |
-
}
|
| 761 |
-
}
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|