| --- |
| 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). |
| |
| |
