High-performance FAQ retrieval using an automatic clustering method of query logs |
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| Authors: | Harksoo Kim Jungyun Seo |
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| Institution: | 1. CIIR, Department of Computer Science, 140 Governors Drive, University of Massachusetts, Amherst, MA, 01003-9264, USA;2. Department of Computer Science and Program of Integrated Biotechnology, Sogang University, Sinsu-dong 1, Mapo-gu, Seoul, 121-742, Korea |
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| Abstract: | To resolve some of lexical disagreement problems between queries and FAQs, we propose a reliable FAQ retrieval system using query log clustering. On indexing time, the proposed system clusters the logs of users’ queries into predefined FAQ categories. To increase the precision and the recall rate of clustering, the proposed system adopts a new similarity measure using a machine readable dictionary. On searching time, the proposed system calculates the similarities between users’ queries and each cluster in order to smooth FAQs. By virtue of the cluster-based retrieval technique, the proposed system could partially bridge lexical chasms between queries and FAQs. In addition, the proposed system outperforms the traditional information retrieval systems in FAQ retrieval. |
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| Keywords: | Lexical disagreement problem Query log clustering FAQ retrieval Cluster-based retrieval |
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