Using ontology-based user preferences to aggregate rank lists in web search

Authors:
Lin Li;Zhenglu Yang;Masaru Kitsuregawa
Affiliations:
Dept. of Info. and Comm. Engineering, University of Tokyo, Japan;Dept. of Info. and Comm. Engineering, University of Tokyo, Japan;Institute of Industrial Science, University of Tokyo, Japan
Venue:
PAKDD'08 Proceedings of the 12th Pacific-Asia conference on Advances in knowledge discovery and data mining
Year:
2008

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Abstract

This paper studies rank aggregation by using ontology-based user preferences in the context of Web search. We introduce a set of techniques to combine the respective rank lists produced by different attributes of user preferences. Furthermore, the learned user preferences are structured as a taxonomic hierarchy (a simple ontology). We use the learned ontology to store the attributes such as, the topics that a user is interested in and the degrees of user interests in these topics. The primary goal of our work is to form a broadly acceptable rank list among these attributes by making use of rank-based aggregation. Experiment results on a real click-through data set show that our user-centered rank aggregation techniques are effective in improving the quality of the Web search in terms of user satisfaction.