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Improving search engines by query clustering.

Authors :
Baeza-Yates, Ricardo
Hurtado, Carlos
Mendoza, Marcelo
Source :
Journal of the American Society for Information Science & Technology. Oct2007, Vol. 58 Issue 12, p1793-1804. 12p. 1 Diagram, 6 Charts, 8 Graphs.
Publication Year :
2007

Abstract

In this paper, we present a framework for clustering Web search engine queries whose aim is to identify groups of queries used to search for similar information on the Web. The framework is based on a novel term vector model of queries that integrates user selections and the content of selected documents extracted from the logs of a search engine. The query representation obtained allows us to treat query clustering similarly to standard document clustering. We study the application of the clustering framework to two problems: relevance ranking boosting and query recommendation. Finally, we evaluate with experiments the effectiveness of our approach. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
15322882
Volume :
58
Issue :
12
Database :
Academic Search Index
Journal :
Journal of the American Society for Information Science & Technology
Publication Type :
Academic Journal
Accession number :
26848038
Full Text :
https://doi.org/10.1002/asi.20627