Related word extraction algorithm for query expansion - An evaluation

Tetsuya Oishi, Tsunenori Mine, Ryuzo Hasegawa, Hiroshi Fujita, Miyuki Koshimura

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

1 被引用数 (Scopus)


When searching for information a user wants, search engines often return lots of results unintended by the user. Query expansion is a promising approach to solve this problem. In the query expansion research, one of the biggest issues is to generate appropriate keywords representing the user's intention. The Related Word Extraction Algorithm (RWEA) we proposed extracts such keywords for the query expansion. In this paper, we evaluate the RWEA through several experiments considering the types of queries given by the users. We compare the RWEA, Robertson's Selection Value (RSV) which is one of the famous relevance feedback methods, and the combination of RWEA and RSV. The results show that as queries become more ambiguous, the advantage of the RWEA becomes higher. From the points of view of query types, the RWEA is appropriate for informational queries and the combined method is for navigational queries. For both query types, RWEA helps to find relevant information.

ホスト出版物のタイトルAdvances in Practical Multi-Agent Systems
編集者Quan Bai
出版ステータス出版済み - 11 4 2010


名前Studies in Computational Intelligence

All Science Journal Classification (ASJC) codes

  • 人工知能


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