Topic Structure Mining based on Wikipedia and Web Search

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1 DEWS2008 A7-5 Wikipedia Web AdamJatowt Wikipedia Web Web Wikipedia Wikipedia Abstract Topic Structure Mining based on Wikipedia and Web Search Makoto NAKATANI, Taro TEZUKA, Adam JATOWT, and Katsumi TANAKA Department of Informatics and Mathematical Science, Faculty of Engineering, Kyoto University Yoshida-honmachi, Sakyo, Kyoto, Japan Department of Social Informatics, Graduate School of Informatics, Kyoto University Yoshida-honmachi, Sakyo, Kyoto, Japan This paper proposes a method for extracting topic terms and analyzing characteristics of topic terms by using the structual features of Wikipedia, the free encyclopedia, and Web search. Existing method can t extract topic terms for multiple terms, and extracted terms contain both general terms and special terms for user s requests. Our method enables to extract topic terms for multiple terms by improving existing methods, and analyze generality and specialty of each topic terms by using the structural features of Wikipedia like sections and links. It supports user s understanding of the topic by showing how widely or narrowly the terms are used. Key words Wikipedia, Topic structure, Topic extraction 1. Web Web Google 1 Yahoo! 2 Web Web Web Web Web 2

Mathematical Science, Faculty of Engineering, Kyoto University Yoshida-honmachi, Sakyo, Kyoto, 606-8501 Japan Department of Social Informatics, Graduate School of Informatics, Kyoto University

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