IR evaluation methods for retrieving highly relevant documents
SIGIR '00 Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval
Rank aggregation methods for the Web
Proceedings of the 10th international conference on World Wide Web
An Approach for Measuring Semantic Similarity between Words Using Multiple Information Sources
IEEE Transactions on Knowledge and Data Engineering
Using ODP metadata to personalize search
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
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This paper is to investigate rank aggregation based on multiple user-centered measures in the context of the web search. We introduce a set of techniques to combine ranking lists in order of user interests termed as a user profile. Moreover, based on the click-history data, a kind of taxonomic hierarchy automatically models the user profile which can include a variety of attributes of user interests. We mainly focus on the topics 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 ranking list, rather than that determined by an individual ranking measure. Experiment results on a real click-history data set show the effectiveness of our aggregation techniques to improve the web search.