Adaptive query refinement based on global and local analysis

Authors:
Chaoyuan Cui;Hanxiong Chen;Kazutaka Furuse;Nobuo Ohbo
Affiliations:
University of Tsukuba, Tsukuba Ibaraki, Japan;University of Tsukuba, Tsukuba Ibaraki, Japan;University of Tsukuba, Tsukuba Ibaraki, Japan;University of Tsukuba, Tsukuba Ibaraki, Japan
Venue:
FSKD'05 Proceedings of the Second international conference on Fuzzy Systems and Knowledge Discovery - Volume Part I
Year:
2005

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Abstract

The goal of information retrieval (IR) is to identify documents which best satisfy users' information need. The task of formulating an effective query is difficult in the sense that it requires users to predict the keywords that will appear in the desired documents. In our study we proposed a method of query refinement by combining candidate keywords with query operators. The method uses the concept Prime Keyword Set, which is a subset of whole keywords and obtained by global analysis of the target database. Considering user's intension we generate rational size of candidates by local analysis based on several specified principles. The experiments are conducted to confirm the effectiveness and efficiency of our proposed method. Moreover, as an extension of our approach an online system is implemented to investigate the feasibility.