Association thesaurus construction methods based on link co-occurrence analysis for wikipedia

  • Authors:

  • Masahiro Ito;Kotaro Nakayama;Takahiro Hara;Shojiro Nishio

  • Affiliations:

  • Osaka University, Osaka, Japan;The University of Tokyo, Tokyo, Japan;Osaka University, Osaka, Japan;Osaka University, Osaka, Japan

  • Venue:
  • Proceedings of the 17th ACM conference on Information and knowledge management
  • Year:
  • 2008

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Abstract

Wikipedia, a huge scale Web based encyclopedia, attracts great attention as an invaluable corpus for knowledge extraction because it has various impressive characteristics such as a huge number of articles, live updates, a dense link structure, brief anchor texts and URL identification for concepts. We have already proved that we can use Wikipedia to construct a huge scale accurate association thesaurus. The association thesaurus we constructed covers almost 1.3 million concepts and its accuracy is proved in detailed experiments. However, we still need scalable methods to analyze the huge number of Web pages and hyperlinks among articles in the Web based encyclopedia. In this paper, we propose a scalable method for constructing an association thesaurus from Wikipedia based on link co-occurrences. Link co-occurrence analysis is more scalable than link structure analysis because it is a one-pass process. We also propose integration method of tfidf and link co-occurrence analysis. Experimental results show that both our proposed methods are more accurate and scalable than conventional methods. Furthermore, the integration of tfidf achieved higher accuracy than using only link co-occurrences.