Add files using upload-large-folder tool

README.md

@@ -0,0 +1,108 @@
+---
+license: other
+license_name: commoncrawl-derived
+license_link: https://commoncrawl.org/terms-of-use
+pretty_name: Common Crawl Host-Graph Embeddings (deg≥8, shallow LP, dim-128)
+tags:
+- common-crawl
+- web-graph
+- graph-embeddings
+- host-graph
+- link-prediction
+task_categories:
+- feature-extraction
+size_categories:
+- 10M<n<100M
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: vectors/emb-*.parquet
+---
+
+# Common Crawl Host-Graph Embeddings — `cc-main-2025-26-nov-dec-jan` (deg≥8, shallow, dim-128)
+
+Dense 128-dimensional embeddings for **52,913,544 web hosts**, learned by link prediction on the
+Common Crawl **host-level hyperlink graph** release `cc-main-2025-26-nov-dec-jan`
+(279.4 M hosts / 13.4 B directed edges). Vectors are **L2-normalized** and served in **float16**;
+similarity is **cosine** (a dot product on the unit vectors).
+
+> **Scope.** These are the **degree ≥ 8** hosts (total in+out degree), a 52.9 M / ~19 % induced
+> subgraph that carries ~97 % of the edges. The low-degree tail of the full 279 M-host graph is
+> **not** in this table — it is intended to be served separately via a domain/metadata fallback.
+
+## What each row is
+
+One host, keyed by two stable string identifiers derived deterministically from the Common Crawl
+host name (no per-release integer ids — those are ephemeral):
+
+| column | type | meaning |
+|---|---|---|
+| `row_id` | int64 | global row index; `shard = row_id // rows_per_shard` |
+| `host_key` | string | forward host, e.g. `www.example.com` (the stable identity key) |
+| `domain_key` | string | registrable domain / PLD (eTLD+1), e.g. `example.com` |
+| `embedding` | `fixed_size_list<float16>[128]` | the L2-normalized vector |
+
+## Files
+
+```
+vectors/emb-00000-of-00014.parquet … emb-00013-of-00014.parquet   # ~1 GB each, 4 M rows/shard
+manifest.json                                                     # schema/model version, per-shard row ranges + SHA-256
+```
+
+Shards are **contiguous row ranges** (not hash-partitioned), so `row_id` order is preserved across
+shards. To locate one host without downloading everything, read only the `host_key`/`row_id`
+columns of the shards (Parquet projects columns), then fetch the single shard
+`row_id // 4_000_000`.
+
+## Usage
+
+Stream as a 🤗 `datasets` table:
+
+```python
+from datasets import load_dataset
+ds = load_dataset("malteos/cc-web-graph-embeddings", split="train", streaming=True)
+row = next(iter(ds))
+print(row["host_key"], len(row["embedding"]))
+```
+
+Materialize a contiguous matrix for FAISS / numpy (cosine = inner product on these unit vectors):
+
+```python
+import numpy as np, pyarrow.parquet as pq, glob
+mats, keys = [], []
+for f in sorted(glob.glob("vectors/emb-*.parquet")):
+    t = pq.read_table(f, columns=["host_key", "embedding"])
+    keys += t["host_key"].to_pylist()
+    mats.append(np.asarray(t["embedding"].to_pylist(), dtype=np.float32))
+X = np.vstack(mats)                      # [52_913_544, 128], already L2-normalized
+```
+
+## Provenance & model
+
+- **Source graph:** Common Crawl host webgraph `cc-main-2025-26-nov-dec-jan`, aggregating crawls
+  **CC-MAIN-2025-47, CC-MAIN-2025-51, CC-MAIN-2026-04**.
+- **Encoder:** shallow (per-node) embedding table trained by link prediction (WholeGraph-sharded,
+  in-batch negatives), `dim=128`, 3 epochs. `model_space_version = cc_deg8_shallow_v1`.
+- **Link-prediction quality (held-out edges):** MRR **0.957**, Hits@1 **0.939**, Hits@10 **0.984**.
+- **Precision:** float16 is the **primary published tier**; the lossless float32 master is archived
+  (for L2-normalized unit vectors fp16's cosine error is ~3–4×10⁻⁵ — negligible for ranking).
+
+## What the embedding captures
+
+Downstream probes show the space encodes **graph structure**, not page content-language:
+topic and spam signals are recoverable from the vectors (topic emb-only logistic-regression
+macro-F1 ≈ 0.39), while **content-language is at the floor** (k-NN ≈ 0.02) — hosts are placed by who
+links to whom, not by the language they publish in. Select on topic/spam utility, not LP MRR alone.
+
+## Limitations
+
+- Degree ≥ 8 hosts only (see Scope). No vectors for the isolated/low-degree tail.
+- Vectors are comparable **only within** `model_space_version`; a retrain / new window bumps it.
+- Identity keys are pure functions of the published (punycode) host string — no IDNA decoding.
+
+## License
+
+Derived from the Common Crawl host webgraph; use is subject to the
+[Common Crawl Terms of Use](https://commoncrawl.org/terms-of-use). The embedding artifact is
+released for research use. *(Set the final license before making this dataset public.)*

manifest.json

@@ -0,0 +1,154 @@
+{
+  "schema_version": "0.1.0",
+  "model_space_version": "cc_deg8_shallow_v1",
+  "release_id": "cc-main-2025-26-nov-dec-jan",
+  "source_crawls": [
+    "CC-MAIN-2025-47",
+    "CC-MAIN-2025-51",
+    "CC-MAIN-2026-04"
+  ],
+  "encoder": "shallow",
+  "dim": 128,
+  "num_rows": 52913544,
+  "rows_per_shard": 4000000,
+  "num_shards": 14,
+  "distance": "cosine",
+  "normalized": true,
+  "input_norm_min_mean_max": [
+    0.00423435540869832,
+    0.7896863222122192,
+    16.95893669128418
+  ],
+  "columns": {
+    "row_id": "int64 (global row index; shard = row_id // rows_per_shard)",
+    "host_key": "str (forward host, contract identity key)",
+    "domain_key": "str (registrable domain / PLD)",
+    "embedding": "fixed_size_list<the set's dtype>[dim]"
+  },
+  "canonical_precision": "float16",
+  "precisions": {
+    "vectors": "float16"
+  },
+  "metrics": {
+    "best_val_mrr": 0.9573509097099304,
+    "test_mrr": 0.9574283957481384,
+    "test_hits@1": 0.938551127910614,
+    "test_hits@10": 0.9841657280921936
+  },
+  "shards": {
+    "vectors": [
+      {
+        "filename": "vectors/emb-00000-of-00014.parquet",
+        "row_start": 0,
+        "row_end": 4000000,
+        "n_rows": 4000000,
+        "bytes": 994153201,
+        "sha256": "e32fa2299222daed7e95a7727f7c1f83c15fa4a5781112d607e91a8f8ea46ad8"
+      },
+      {
+        "filename": "vectors/emb-00001-of-00014.parquet",
+        "row_start": 4000000,
+        "row_end": 8000000,
+        "n_rows": 4000000,
+        "bytes": 996320017,
+        "sha256": "1ebd23f6378740bc63244c893403f021f42de88e871f6432cf0052611635994f"
+      },
+      {
+        "filename": "vectors/emb-00002-of-00014.parquet",
+        "row_start": 8000000,
+        "row_end": 12000000,
+        "n_rows": 4000000,
+        "bytes": 988733128,
+        "sha256": "8e11b1f2070f1fde071eb63199ff060908f0c2570ae24f97fb250286192e2922"
+      },
+      {
+        "filename": "vectors/emb-00003-of-00014.parquet",
+        "row_start": 12000000,
+        "row_end": 16000000,
+        "n_rows": 4000000,
+        "bytes": 993631056,
+        "sha256": "49da7772ce6ec0f3579252165dadd52243546ff413e6c6a895fd70464d959ec9"
+      },
+      {
+        "filename": "vectors/emb-00004-of-00014.parquet",
+        "row_start": 16000000,
+        "row_end": 20000000,
+        "n_rows": 4000000,
+        "bytes": 991434583,
+        "sha256": "00f2bb1e2800d4219929e93b9eaf49f42a788f98588f0e5f93b92d5937d9ac66"
+      },
+      {
+        "filename": "vectors/emb-00005-of-00014.parquet",
+        "row_start": 20000000,
+        "row_end": 24000000,
+        "n_rows": 4000000,
+        "bytes": 994561044,
+        "sha256": "1cde6b5427eee1434438be6271aeb77e7aac8c18cc71ac3f705c33656efdda6f"
+      },
+      {
+        "filename": "vectors/emb-00006-of-00014.parquet",
+        "row_start": 24000000,
+        "row_end": 28000000,
+        "n_rows": 4000000,
+        "bytes": 996913787,
+        "sha256": "9aca2696429b4044e9da3137bc83b73655210c3e1d5e0f924f2117c0a35a3e54"
+      },
+      {
+        "filename": "vectors/emb-00007-of-00014.parquet",
+        "row_start": 28000000,
+        "row_end": 32000000,
+        "n_rows": 4000000,
+        "bytes": 991022923,
+        "sha256": "277843c663d5ffe40d6faa75fee256ce1583ef0f40d428db7defcfbf821b7363"
+      },
+      {
+        "filename": "vectors/emb-00008-of-00014.parquet",
+        "row_start": 32000000,
+        "row_end": 36000000,
+        "n_rows": 4000000,
+        "bytes": 1000569253,
+        "sha256": "c1f5a7b8b288b837c7004ed3cc6b028a26118d82f52e95100f4afe4102b23d7d"
+      },
+      {
+        "filename": "vectors/emb-00009-of-00014.parquet",
+        "row_start": 36000000,
+        "row_end": 40000000,
+        "n_rows": 4000000,
+        "bytes": 996032003,
+        "sha256": "1693c6a90e0306d141398b8060941b231316b17ee1fca4e92d7afc923492ba46"
+      },
+      {
+        "filename": "vectors/emb-00010-of-00014.parquet",
+        "row_start": 40000000,
+        "row_end": 44000000,
+        "n_rows": 4000000,
+        "bytes": 992647038,
+        "sha256": "fc2b663bd6fc41b03d3f0cc52c1db36d6f6c4b71845461fb93c9bfdd3c37acdf"
+      },
+      {
+        "filename": "vectors/emb-00011-of-00014.parquet",
+        "row_start": 44000000,
+        "row_end": 48000000,
+        "n_rows": 4000000,
+        "bytes": 994504489,
+        "sha256": "c4dbf2f84830d1229f5b9c37e7322f21e790256121413bccb98dbfa9c01dc136"
+      },
+      {
+        "filename": "vectors/emb-00012-of-00014.parquet",
+        "row_start": 48000000,
+        "row_end": 52000000,
+        "n_rows": 4000000,
+        "bytes": 990996371,
+        "sha256": "85ec3c5f5a8c52453554ef9b67d64751122390cd682b2966b9eed1d98518f052"
+      },
+      {
+        "filename": "vectors/emb-00013-of-00014.parquet",
+        "row_start": 52000000,
+        "row_end": 52913544,
+        "n_rows": 913544,
+        "bytes": 227094665,
+        "sha256": "ae465a772e20963c894e5ecbfaaff6bfa39b942962d8df0aa9293625fbb326e0"
+      }
+    ]
+  }
+}

vectors/emb-00000-of-00014.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e32fa2299222daed7e95a7727f7c1f83c15fa4a5781112d607e91a8f8ea46ad8
+size 994153201

vectors/emb-00001-of-00014.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:1ebd23f6378740bc63244c893403f021f42de88e871f6432cf0052611635994f
+size 996320017

vectors/emb-00002-of-00014.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:8e11b1f2070f1fde071eb63199ff060908f0c2570ae24f97fb250286192e2922
+size 988733128

vectors/emb-00003-of-00014.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:49da7772ce6ec0f3579252165dadd52243546ff413e6c6a895fd70464d959ec9
+size 993631056

vectors/emb-00004-of-00014.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:00f2bb1e2800d4219929e93b9eaf49f42a788f98588f0e5f93b92d5937d9ac66
+size 991434583

vectors/emb-00005-of-00014.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:1cde6b5427eee1434438be6271aeb77e7aac8c18cc71ac3f705c33656efdda6f
+size 994561044

vectors/emb-00006-of-00014.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9aca2696429b4044e9da3137bc83b73655210c3e1d5e0f924f2117c0a35a3e54
+size 996913787

vectors/emb-00007-of-00014.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:277843c663d5ffe40d6faa75fee256ce1583ef0f40d428db7defcfbf821b7363
+size 991022923

vectors/emb-00008-of-00014.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c1f5a7b8b288b837c7004ed3cc6b028a26118d82f52e95100f4afe4102b23d7d
+size 1000569253

vectors/emb-00009-of-00014.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:1693c6a90e0306d141398b8060941b231316b17ee1fca4e92d7afc923492ba46
+size 996032003

vectors/emb-00010-of-00014.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:fc2b663bd6fc41b03d3f0cc52c1db36d6f6c4b71845461fb93c9bfdd3c37acdf
+size 992647038

vectors/emb-00011-of-00014.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c4dbf2f84830d1229f5b9c37e7322f21e790256121413bccb98dbfa9c01dc136
+size 994504489

vectors/emb-00012-of-00014.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:85ec3c5f5a8c52453554ef9b67d64751122390cd682b2966b9eed1d98518f052
+size 990996371

vectors/emb-00013-of-00014.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ae465a772e20963c894e5ecbfaaff6bfa39b942962d8df0aa9293625fbb326e0
+size 227094665