--- 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.
Click here for the table | `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 |
## 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).