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.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.