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language:
- en
license: odc-by
tags:
- document-classification
- text-classification
- web-pages
configs:
- config_name: All
default: true
data_files:
- path:
- All/train.jsonl.zst
split: train
- path:
- All/test.jsonl.zst
split: test
- config_name: ArtDesign
data_files:
- path:
- ArtDesign.jsonl.zst
split: train
- config_name: ArtsEntertainment
data_files:
- path:
- ArtsEntertainment.jsonl.zst
split: train
- config_name: AutosVehicles
data_files:
- path:
- AutosVehicles.jsonl.zst
split: train
- config_name: BeautyFitness
data_files:
- path:
- BeautyFitness.jsonl.zst
split: train
- config_name: BooksLiterature
data_files:
- path:
- BooksLiterature.jsonl.zst
split: train
- config_name: BusinessIndustry
data_files:
- path:
- BusinessIndustry.jsonl.zst
split: train
- config_name: EducationCareers
data_files:
- path:
- EducationCareers.jsonl.zst
split: train
- config_name: ElectronicsHardware
data_files:
- path:
- ElectronicsHardware.jsonl.zst
split: train
- config_name: FinanceInvestment
data_files:
- path:
- FinanceInvestment.jsonl.zst
split: train
- config_name: FoodDrink
data_files:
- path:
- FoodDrink.jsonl.zst
split: train
- config_name: GamesRecreation
data_files:
- path:
- GamesRecreation.jsonl.zst
split: train
- config_name: HealthWellness
data_files:
- path:
- HealthWellness.jsonl.zst
split: train
- config_name: HobbiesLeisure
data_files:
- path:
- HobbiesLeisure.jsonl.zst
split: train
- config_name: HomeGardening
data_files:
- path:
- HomeGardening.jsonl.zst
split: train
- config_name: IndustrialManufacturing
data_files:
- path:
- IndustrialManufacturing.jsonl.zst
split: train
- config_name: InternetTelecom
data_files:
- path:
- InternetTelecom.jsonl.zst
split: train
- config_name: LawGovernment
data_files:
- path:
- LawGovernment.jsonl.zst
split: train
- config_name: NewsPolitics
data_files:
- path:
- NewsPolitics.jsonl.zst
split: train
- config_name: PeopleSociety
data_files:
- path:
- PeopleSociety.jsonl.zst
split: train
- config_name: RealEstateProperty
data_files:
- path:
- RealEstateProperty.jsonl.zst
split: train
- config_name: ReligionSociety
data_files:
- path:
- ReligionSociety.jsonl.zst
split: train
- config_name: ScienceResearch
data_files:
- path:
- ScienceResearch.jsonl.zst
split: train
- config_name: ShoppingRetail
data_files:
- path:
- ShoppingRetail.jsonl.zst
split: train
- config_name: SoftwareApplications
data_files:
- path:
- SoftwareApplications.jsonl.zst
split: train
- config_name: SoftwareEngineering
data_files:
- path:
- SoftwareEngineering.jsonl.zst
split: train
- config_name: SportsAthletics
data_files:
- path:
- SportsAthletics.jsonl.zst
split: train
- config_name: TravelTransportation
data_files:
- path:
- TravelTransportation.jsonl.zst
split: train
---
# English Document Topic Classification Dataset
English-language web pages classified by document topic, designed to train robust text classifiers and provide ready-to-use data for specific web topics.
* **Purpose:** Train generalized document classifiers or extract clean, single-topic corpora for specific downstream tasks.
* **Configurations:** Each document topic is available in its own dedicated dataset configuration (e.g., `HomeGardening`, `GamesRecreation`).
* **Splits:** The `All` configuration contains every document topic combined, featuring a 10% stratified test split.
## Curation & Filtering Pipeline
This dataset is derived from a subset of the first 1 million rows of [`allenai/c4`](https://huggingface.co/datasets/allenai/c4), utilizing annotations from [`agentlans/en-document-classification`](https://huggingface.co/datasets/agentlans/en-document-classification).
Samples are included only when the `nvidia_domain` field matches `weborganizer_topic` according to the following mapping.
These 27 categories cover 62% of the samples from the original dataset.
<details>
<summary>Click here for the table</summary>
| `nvidia_domain` | `weborganizer_topic` | Label |
|---|---|---|
| Arts_and_Entertainment | Entertainment | Arts & Entertainment |
| Health | Health | Health & Wellness |
| Home_and_Garden | Home & Hobbies | Home & Gardening |
| Jobs_and_Education | Education & Jobs | Education & Careers |
| Sports | Sports & Fitness | Sports & Athletics |
| Food_and_Drink | Food & Dining | Food & Drink |
| Business_and_Industrial | Finance & Business | Business & Industry |
| Travel_and_Transportation | Travel & Tourism | Travel & Transportation |
| Finance | Finance & Business | Finance & Investment |
| Games | Games | Games & Recreation |
| People_and_Society | Religion | Religion & Society |
| Arts_and_Entertainment | Art & Design | Art & Design |
| Autos_and_Vehicles | Transportation | Autos & Vehicles |
| Computers_and_Electronics | Electronics & Hardare | Electronics & Hardware |
| Business_and_Industrial | Industrial | Industrial & Manufacturing |
| Computers_and_Electronics | Software Development | Software Engineering |
| Real_Estate | Home & Hobbies | Real Estate & Property |
| News | Politics | News & Politics |
| Beauty_and_Fitness | Fashion & Beauty | Beauty & Fitness |
| Computers_and_Electronics | Software | Software Applications |
| Shopping | Fashion & Beauty | Shopping & Retail |
| Science | Science, Math & Technology | Science & Research |
| Law_and_Government | Crime & Law | Law & Government |
| Books_and_Literature | Literature | Books & Literature |
| Internet_and_Telecom | Software | Internet & Telecom |
| Hobbies_and_Leisure | Home & Hobbies | Hobbies & Leisure |
| People_and_Society | Social Life | People & Society |
</details>
## Class Distribution (`All` Split)
| Label | Train | Test | Total |
|-------|-------|------|-------|
| Art & Design | 18889 | 2099 | 20988 |
| Arts & Entertainment | 46263 | 5140 | 51403 |
| Autos & Vehicles | 18750 | 2083 | 20833 |
| Beauty & Fitness | 15036 | 1671 | 16707 |
| Books & Literature | 11836 | 1315 | 13151 |
| Business & Industry | 28997 | 3222 | 32219 |
| Education & Careers | 34707 | 3856 | 38563 |
| Electronics & Hardware | 17651 | 1961 | 19612 |
| Finance & Investment | 20910 | 2323 | 23233 |
| Food & Drink | 32989 | 3665 | 36654 |
| Games & Recreation | 19046 | 2116 | 21162 |
| Health & Wellness | 40407 | 4490 | 44897 |
| Hobbies & Leisure | 9158 | 1018 | 10176 |
| Home & Gardening | 39439 | 4382 | 43821 |
| Industrial & Manufacturing | 16477 | 1831 | 18308 |
| Internet & Telecom | 10404 | 1156 | 11560 |
| Law & Government | 12108 | 1345 | 13453 |
| News & Politics | 15207 | 1690 | 16897 |
| People & Society | 8029 | 892 | 8921 |
| Real Estate & Property | 15841 | 1760 | 17601 |
| Religion & Society | 18958 | 2107 | 21065 |
| Science & Research | 12203 | 1356 | 13559 |
| Shopping & Retail | 13245 | 1472 | 14717 |
| Software Applications | 14332 | 1593 | 15925 |
| Software Engineering | 15864 | 1763 | 17627 |
| Sports & Athletics | 34525 | 3836 | 38361 |
| Travel & Transportation | 22805 | 2534 | 25339 |
| **Total** | 564076 | 62676 | 626752 |
## Licensing
Distributed under the Open Data Commons Attribution License (ODC-BY), matching the licensing terms of upstream sources [`allenai/c4`](https://huggingface.co/datasets/allenai/c4) and [`agentlans/en-document-classification`](https://www.google.com/search?q=https://huggingface.co/datasets/agentlans/en-document-classification).
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