Category Classification and Topic Discovery of Japanese and English News Articles | Zendy

David B. Bracewell | Zendy; Jiajun Yan | Zendy; Fuji Ren | Zendy; Shingo Kuroiwa | Zendy

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Category Classification and Topic Discovery of Japanese and English News Articles

Author(s) -

David B. Bracewell,

Jiajun Yan,

Fuji Ren,

Shingo Kuroiwa

Publication year - 2009

Publication title -

electronic notes in theoretical computer science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.242

H-Index - 60

ISSN - 1571-0661

DOI - 10.1016/j.entcs.2008.12.066

Subject(s) - computer science , information retrieval , statistical classification , document classification , precision and recall , natural language processing , library classification , artificial intelligence , world wide web

This paper presents algorithms for topic analysis of news articles. Topic analysis entails category classification and topic discovery and classification. Dealing with news has special requirements that standard classification approaches typically cannot handle. The algorithms proposed in this paper are able to do online training for both category and topic classification as well as discover new topics as they arise. Both algorithms are based on a keyword extraction algorithm that is applicable to any language that has basic morphological analysis tools. As such, both the category classification and topic discovery and classification algorithms can be easily used by multiple languages. Through experimentation the algorithms are shown to have high precision and recall in tests on English and Japanese

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