
Dataset:
Dataset Card for "ag_news"
Dataset Summary
AG is a collection of more than 1 million news articles. News articles have been gathered from more than 2000 news sources by ComeToMyHead in more than 1 year of activity. ComeToMyHead is an academic news search engine which has been running since July, 2004. The dataset is provided by the academic comunity for research purposes in data mining (clustering, classification, etc), information retrieval (ranking, search, etc), xml, data compression, data streaming, and any other non-commercial activity. For more information, please refer to the link http://www.di.unipi.it/~gulli/AG_corpus_of_news_articles.html .
The AG's news topic classification dataset is constructed by Xiang Zhang (xiang.zhang@nyu.edu) from the dataset above. It is used as a text classification benchmark in the following paper: Xiang Zhang, Junbo Zhao, Yann LeCun. Character-level Convolutional Networks for Text Classification. Advances in Neural Information Processing Systems 28 (NIPS 2015).
Supported Tasks
Languages
Dataset Structure
We show detailed information for up to 5 configurations of the dataset.
Data Instances
default
- Size of downloaded dataset files: 29.88 MB
- Size of the generated dataset: 30.23 MB
- Total amount of disk used: 60.10 MB
An example of 'train' looks as follows.
{
"label": 3,
"text": "New iPad released Just like every other September, this one is no different. Apple is planning to release a bigger, heavier, fatter iPad that..."
}
Data Fields
The data fields are the same among all splits.
default
text
: astring
feature.label
: a classification label, with possible values includingWorld
(0),Sports
(1),Business
(2),Sci/Tech
(3).
Data Splits Sample Size
name | train | test |
---|---|---|
default | 120000 | 7600 |
Dataset Creation
Curation Rationale
Source Data
Annotations
Personal and Sensitive Information
Considerations for Using the Data
Social Impact of Dataset
Discussion of Biases
Other Known Limitations
Additional Information
Dataset Curators
Licensing Information
Citation Information
@inproceedings{Zhang2015CharacterlevelCN,
title={Character-level Convolutional Networks for Text Classification},
author={Xiang Zhang and Junbo Jake Zhao and Yann LeCun},
booktitle={NIPS},
year={2015}
}
Contributions
Thanks to @jxmorris12, @thomwolf, @lhoestq, @lewtun for adding this dataset.