Datasets:
language:
- ko
size_categories:
- 100K<n<1M
task_categories:
- text-classification
task_ids:
- topic-classification
paperswithcode_id: ag-news
pretty_name: AG’s News Corpus
license: unknown
dataset_info:
features:
- name: text
dtype: string
- name: label
dtype:
class_label:
names:
'0': World
'1': Sports
'2': Business
'3': Sci/Tech
- name: data_index_by_user
dtype: int32
splits:
- name: train
num_bytes: 35075728
num_examples: 120000
- name: test
num_bytes: 2195191
num_examples: 7600
download_size: 22724153
dataset_size: 37270919
Dataset Card for ag_news
Licensing Information & 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 ([email protected]) 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).
Source Data 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}
}