1. Improving search engines by query clustering.
- Author
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Baeza-Yates, Ricardo, Hurtado, Carlos, and Mendoza, Marcelo
- Subjects
- *
PAPER , *EVALUATION , *SEARCH engines , *DOCUMENT clustering , *DATABASE searching , *INTERNET searching , *INFORMATION services , *ONLINE information services , *DATA mining , *WEBSITES - 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]
- Published
- 2007
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