Reuters27000

Published: 3 November 2016| Version 1 | DOI: 10.17632/3cw44dk29f.1
Contributors:
Marcos Mouriño García,
,

Description

To create the corpus, first we download from Reuters website 27,000 random news articles (HTML webpages) classified under each one of the following categories: Health, Art, Politics, Sports, Science, Technology, Economy, and Business. Next, we extracting from each article the title, the body and the category to which it belongs to. Finally, we stored in our database the title, body and category for each article that was downloaded. As a results—after removing duplicates—we obtained a corpus that comprises 23,863 documents that we randomly split in a training sequence that comprises 14,356 documents and a test sequence composed of 9,507 documents.

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Steps to reproduce

To create the corpus, first we download from Reuters website 27,000 random news articles (HTML webpages) classified under each one of the following categories: Health, Art, Politics, Sports, Science, Technology, Economy, and Business. Next, we extracting from each article the title, the body and the category to which it belongs to. Finally, we stored in our database the title, body and category for each article that was downloaded. As a results—after removing duplicates—we obtained a corpus that comprises 23,863 documents that we randomly split in a training sequence that comprises 14,356 documents and a test sequence composed of 9,507 documents.

Categories

Data Mining, Biological Classification

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