Improving FAQ retrieval using query log clustering in latent semantic space

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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. © Springer-Verlag Berlin Heidelberg 2005.

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APA

Kim, H., Lee, H., & Seo, J. (2005). Improving FAQ retrieval using query log clustering in latent semantic space. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3689 LNCS, pp. 233–245). Springer Verlag. https://doi.org/10.1007/11562382_18

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