Improving FAQ retrieval using query log clustering in latent semantic space

Authors:
Harksoo Kim;Hyunjung Lee;Jungyun Seo
Affiliations:
CIIR in UMass, Amherst, LGRC A341, Computer Science Department, University of Massachusetts, Amherst, MA;Department of Computer Science, Sogang University, Seoul, Korea;Department of Computer Science and Program of Integrated Biotechnology, Sogang University, Seoul, Korea
Venue:
AIRS'05 Proceedings of the Second Asia conference on Asia Information Retrieval Technology
Year:
2005

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Abstract

Lexical disagreement problems often occur in FAQ retrieval because FAQs unlike general documents consist of just one or two sentences. To resolve lexical disagreement problems, we propose a high-performance FAQ retrieval system using query log clustering. During indexing time, using latent semantic analysis techniques, the proposed system classifies and groups the logs of users’ queries into predefined FAQ categories. During retrieval time, the proposed system uses the query log clusters as a form of FAQ smoothing. In our experiment, we found that the proposed system could resolve some lexical disagreement problems between queries and FAQs.