Hugging Face's logo

Datasets:
ucirvine
/
reuters21578

Languages:
English
License:
Dataset card Files Community
3
Dataset Viewer
Full Screen

The viewer is disabled because this dataset repo requires arbitrary Python code execution. Please consider removing the loading script and relying on automated data support (you can use convert_to_parquet from the datasets library). If this is not possible, please open a discussion for direct help.

Dataset Card for "reuters21578"

Dataset Summary

The Reuters-21578 dataset is one of the most widely used data collections for text categorization research. It is collected from the Reuters financial newswire service in 1987.

Supported Tasks and Leaderboards

More Information Needed

Languages

More Information Needed

Dataset Structure

Data Instances

ModApte

  • Size of downloaded dataset files: 8.15 MB
  • Size of the generated dataset: 13.05 MB
  • Total amount of disk used: 21.21 MB

An example of 'train' looks as follows.

This example was too long and was cropped:

{
    "cgis_split": "\"TRAINING-SET\"",
    "date": "19-MAR-1987 06:17:22.36",
    "exchanges": [],
    "lewis_split": "\"TRAIN\"",
    "new_id": "\"7001\"",
    "old_id": "\"11914\"",
    "orgs": [],
    "people": [],
    "places": ["australia"],
    "text": "\"Media group John Fairfax Ltd <FFXA.S>\\nsaid that its flat first half net profit partly reflected the\\nimpact of changes in t...",
    "title": "FAIRFAX SAYS HIGHER TAX HITS FIRST HALF EARNINGS",
    "topics": ["earn"]
}

ModHayes

  • Size of downloaded dataset files: 8.15 MB
  • Size of the generated dataset: 19.79 MB
  • Total amount of disk used: 27.93 MB

An example of 'train' looks as follows.

This example was too long and was cropped:

{
    "cgis_split": "\"TRAINING-SET\"",
    "date": "19-OCT-1987 23:49:31.45",
    "exchanges": [],
    "lewis_split": "\"TEST\"",
    "new_id": "\"20001\"",
    "old_id": "\"20596\"",
    "orgs": [],
    "people": [],
    "places": ["japan", "usa"],
    "text": "\"If the dollar goes the way of Wall Street,\\nJapanese will finally move out of dollar investments in a\\nserious way, Japan inves...",
    "title": "IF DOLLAR FOLLOWS WALL STREET JAPANESE WILL DIVEST",
    "topics": ["money-fx"]
}

ModLewis

  • Size of downloaded dataset files: 8.15 MB
  • Size of the generated dataset: 19.38 MB
  • Total amount of disk used: 27.54 MB

An example of 'train' looks as follows.

This example was too long and was cropped:

{
    "cgis_split": "\"TRAINING-SET\"",
    "date": "19-MAR-1987 06:17:22.36",
    "exchanges": [],
    "lewis_split": "\"TRAIN\"",
    "new_id": "\"7001\"",
    "old_id": "\"11914\"",
    "orgs": [],
    "people": [],
    "places": ["australia"],
    "text": "\"Media group John Fairfax Ltd <FFXA.S>\\nsaid that its flat first half net profit partly reflected the\\nimpact of changes in t...",
    "title": "FAIRFAX SAYS HIGHER TAX HITS FIRST HALF EARNINGS",
    "topics": ["earn"]
}

Data Fields

The data fields are the same among all splits.

ModApte

  • text: a string feature.
  • topics: a list of string features.
  • lewis_split: a string feature.
  • cgis_split: a string feature.
  • old_id: a string feature.
  • new_id: a string feature.
  • places: a list of string features.
  • people: a list of string features.
  • orgs: a list of string features.
  • exchanges: a list of string features.
  • date: a string feature.
  • title: a string feature.

ModHayes

  • text: a string feature.
  • topics: a list of string features.
  • lewis_split: a string feature.
  • cgis_split: a string feature.
  • old_id: a string feature.
  • new_id: a string feature.
  • places: a list of string features.
  • people: a list of string features.
  • orgs: a list of string features.
  • exchanges: a list of string features.
  • date: a string feature.
  • title: a string feature.

ModLewis

  • text: a string feature.
  • topics: a list of string features.
  • lewis_split: a string feature.
  • cgis_split: a string feature.
  • old_id: a string feature.
  • new_id: a string feature.
  • places: a list of string features.
  • people: a list of string features.
  • orgs: a list of string features.
  • exchanges: a list of string features.
  • date: a string feature.
  • title: a string feature.

Data Splits

ModApte

train unused test
ModApte 8762 720 3009

ModHayes

train test
ModHayes 18323 720

ModLewis

train unused test
ModLewis 12449 720 5458

Dataset Creation

Curation Rationale

More Information Needed

Source Data

Initial Data Collection and Normalization

More Information Needed

Who are the source language producers?

More Information Needed

Annotations

Annotation process

More Information Needed

Who are the annotators?

More Information Needed

Personal and Sensitive Information

More Information Needed

Considerations for Using the Data

Social Impact of Dataset

More Information Needed

Discussion of Biases

More Information Needed

Other Known Limitations

More Information Needed

Additional Information

Dataset Curators

More Information Needed

Licensing Information

According to the dataset website (https://archive.ics.uci.edu/dataset/137/reuters+21578+text+categorization+collection), this dataset is licensed under Creative Commons Attribution 4.0 International (C BY 4.0) license.

However, the source data file contains a README.txt file with the following information under the Copyright & Notification section:

The copyright for the text of newswire articles and Reuters annotations in the Reuters-21578 collection resides with Reuters Ltd. Reuters Ltd. and Carnegie Group, Inc. have agreed to allow the free distribution of this data for research purposes only. If you publish results based on this data set, please acknowledge its use, refer to the data set by the name "Reuters-21578, Distribution 1.0", and inform your readers of the current location of the data set (see "Availability & Questions").

Citation Information 

@article{APTE94,
author = {Chidanand Apt{'{e}} and Fred Damerau and Sholom M. Weiss},
title = {Automated Learning of Decision Rules for Text Categorization},
journal = {ACM Transactions on Information Systems},
year = {1994},
note = {To appear.}
}

@inproceedings{APTE94b,
author = {Chidanand Apt{'{e}} and Fred Damerau and Sholom M. Weiss},
title = {Toward Language Independent Automated Learning of Text Categorization Models},
booktitle = {sigir94},
year = {1994},
note = {To appear.}
}

@inproceedings{HAYES8},
author = {Philip J. Hayes and Peggy M. Anderson and Irene B. Nirenburg and
Linda M. Schmandt},
title = {{TCS}: A Shell for Content-Based Text Categorization},
booktitle = {IEEE Conference on Artificial Intelligence Applications},
year = {1990}
}

@inproceedings{HAYES90b,
author = {Philip J. Hayes and Steven P. Weinstein},
title = {{CONSTRUE/TIS:} A System for Content-Based Indexing of a
Database of News Stories},
booktitle = {Second Annual Conference on Innovative Applications of
Artificial Intelligence},
year = {1990}
}

@incollection{HAYES92 ,
author = {Philip J. Hayes},
title = {Intelligent High-Volume Text Processing using Shallow,
Domain-Specific Techniques},
booktitle = {Text-Based Intelligent Systems},
publisher = {Lawrence Erlbaum},
address =  {Hillsdale, NJ},
year = {1992},
editor = {Paul S. Jacobs}
}

@inproceedings{LEWIS91c ,
author = {David D. Lewis},
title = {Evaluating Text Categorization},
booktitle = {Proceedings of Speech and Natural Language Workshop},
year = {1991},
month = {feb},
organization = {Defense Advanced Research Projects Agency},
publisher = {Morgan Kaufmann},
pages = {312--318}

}

@phdthesis{LEWIS91d,
author = {David Dolan Lewis},
title = {Representation and Learning in Information Retrieval},
school = {Computer Science Dept.; Univ. of Massachusetts; Amherst, MA 01003},
year = 1992},
note = {Technical Report 91--93.}
}

@inproceedings{LEWIS91e,
author = {David D. Lewis},
title = {Data Extraction as Text Categorization: An Experiment with
the {MUC-3} Corpus},
booktitle = {Proceedings of the Third Message Understanding Evaluation
and Conference},
year = {1991},
month = {may},
organization = {Defense Advanced Research Projects Agency},
publisher = {Morgan Kaufmann},
address = {Los Altos, CA}

}

@inproceedings{LEWIS92b,
author = {David D. Lewis},
title = {An Evaluation of Phrasal and Clustered Representations on a Text
Categorization Task},
booktitle = {Fifteenth Annual International ACM SIGIR Conference on
Research and Development in Information Retrieval},
year = {1992},
pages = {37--50}
}

@inproceedings{LEWIS92d ,
author = {David D. Lewis and Richard M. Tong},
title = {Text Filtering in {MUC-3} and {MUC-4}},
booktitle = {Proceedings of the Fourth Message Understanding Conference ({MUC-4})},
year = {1992},
month = {jun},
organization = {Defense Advanced Research Projects Agency},
publisher = {Morgan Kaufmann},
address = {Los Altos, CA}
}

@inproceedings{LEWIS92e,
author = {David D. Lewis},
title = {Feature Selection and Feature Extraction for Text Categorization},
booktitle = {Proceedings of Speech and Natural Language Workshop},
year = {1992},
month = {feb} ,
organization = {Defense Advanced Research Projects Agency},
publisher = {Morgan Kaufmann},
pages = {212--217}
}

@inproceedings{LEWIS94b,
author = {David D. Lewis and Marc Ringuette},
title = {A Comparison of Two Learning Algorithms for Text Categorization},
booktitle = {Symposium on Document Analysis and Information Retrieval},
year = {1994},
organization = {ISRI; Univ. of Nevada, Las Vegas},
address = {Las Vegas, NV},
month = {apr},
pages = {81--93}
}

@article{LEWIS94d,
author = {David D. Lewis and Philip J. Hayes},
title = {Guest Editorial},
journal = {ACM Transactions on Information Systems},
year = {1994},
volume  = {12},
number  = {3},
pages = {231},
month = {jul}
}

@article{SPARCKJONES76,
author = {K. {Sparck Jones} and  C. J. {van Rijsbergen}},
title =  {Information Retrieval Test Collections},
journal = {Journal of Documentation},
year = {1976},
volume = {32},
number = {1},
pages = {59--75}
}

@book{WEISS91,
author = {Sholom M. Weiss and Casimir A. Kulikowski},
title = {Computer Systems That Learn},
publisher = {Morgan Kaufmann},
year = {1991},
address = {San Mateo, CA}
}

Contributions

Thanks to @jplu, @jbragg, @thomwolf, @mariamabarham, @lhoestq for adding this dataset.

Downloads last month
1,846
Edit dataset card Papers with Code
Homepage:
archive.ics.uci.edu
Size of downloaded dataset files:
24.45 MB

Models trained or fine-tuned on ucirvine/reuters21578