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http://dx.doi.org/10.7840/KICS.2012.37.7C.619

An Efficient Extended Query Suggestion System Using the Analysis of Users' Query Patterns  

Kim, Young-An (국방대학교 국방과학학과)
Park, Gun-Woo (육군 종합보급창)
Abstract
With the service suggesting additional extended or related query, search engines aim to provide their users more convenience. The extended or related query suggestion service based on popularity, or by how many people have searched on web using the query, has limitations to elevate users' satisfaction, because each user's preference and interests differ. This paper will demonstrate the design and realization of the system that suggests extended query appropriate for users' demands, and also an improvement in the computing process between entering the first search word and the subsequent extension to the related themes. According to the evaluation the proposed system suggested 41% more extended or related query than when searching on Google, and 48% more than on Yahoo. Also by improving the shortcomings of the extended or related query system based on general popularity rather than each user's preference, the new system enhanced users' convenience further.
Keywords
Search engines; Related query; Extended query; Users' convenience; Query pattern;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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1 Broder, A., "A Taxonomy of Web Search", SIGAR Forum Vol. 36, No. 2, 2002.
2 Hyungil Kim, Juntae Kim "Improving Performance of Web Search using The User Preference in Query Word Senses", KIISE Vol. 31, No. 8, 2004.   과학기술학회마을
3 Mun HyeonJeong, Lee SuJin, "A Personalized Concept-based Retrieval technique Using Domain Ontology", CALS/EC, Vol. 12, No. 3, 2006.
4 Zhongming Mai, Gautam Pant, Olivia R. Liu Sheng., "Interest-based personalized search", ACM Transactions on Information systems, Vol.25 Issue 1, 2007.
5 AOL Query Set, http://www.gregsadesky.com/aol-date
6 NAVER, http://www.help.naver/service/main.service
7 P. Wallis. J. A. Tom, "Relevace judgement for accessing recall", Information Processing & Management 32, 1998.
8 Teevan, J., Dumais, S. T., "Presonalizing search via automated analysis of interests and activities" SiGIR Coference, 2005.
9 Jihye Kim, Hyun-min Kim "Introduction to Concept in Association Rule Mining", KCC 2002, Vol. 29, No. 1, 2002.   과학기술학회마을
10 Hwan-Seung Yong, "DATA Mining", Infinitebooks, 2007.
11 J. R. Wen, J. Y. Nie and H. J. Zhang. "Clustering user queries of a Search Engine". In Proceedings of the Internation World Wide Web conference, 2001.