Guided Navigation Using Query Log Mining through Query Expansion

We introduce a method to help people to refine their search queries based on other people's similar queries. We compared two different methods of collaborative filtering on search logs of a popular e-commerce site to do query expansion. In item-based method, by identifying similarities between...

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Bibliographic Details
Main Authors: Yurekli, B., Capan, G., Yilmazel, B., Yilmazel, O.
Format: Conference Proceeding
Language:English
Subjects:
Collaboration
Computer networks
Computer security
Feedback
Filtering
guided navigation
Indexing
Navigation
query expansion
query log mining
Search engines
System performance
Thesauri
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Description
Summary:We introduce a method to help people to refine their search queries based on other people's similar queries. We compared two different methods of collaborative filtering on search logs of a popular e-commerce site to do query expansion. In item-based method, by identifying similarities between different items, and in user-based method, by identifying similarities between different users, we compute recommendations for users. The experimental results show that item-based query expansion method provides better performance than the user-based method. While the user-based method improved the system performance 20%, the item-based method provided success of 73%. Also, item-based method recommended better expansion terms than the user-based method, which is important in helping Web users to easily access information needs by formulating qualified queries. This document is a comparison of these two methods, and their effects on system performance.
DOI:10.1109/NSS.2009.27