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A large-scale evaluation and analysis of personalized search strategies

Published:08 May 2007Publication History

ABSTRACT

Although personalized search has been proposed for many years and many personalization strategies have been investigated, it is still unclear whether personalization is consistently effective on different queries for different users, and under different search contexts. In this paper, we study this problem and get some preliminary conclusions. We present a large-scale evaluation framework for personalized search based on query logs, and then evaluate five personalized search strategies (including two click-based and three profile-based ones) using 12-day MSN query logs. By analyzing the results, we reveal that personalized search has significant improvement over common web search on some queries but it also has little effect on other queries (e.g., queries with small click entropy). It even harms search accuracy under some situations. Furthermore, we show that straightforward click-based personalization strategies perform consistently and considerably well, while profile-based ones are unstable in our experiments. We also reveal that both long-term and short-term contexts are very important in improving search performance for profile-based personalized search strategies.

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            cover image ACM Conferences
            WWW '07: Proceedings of the 16th international conference on World Wide Web
            May 2007
            1382 pages
            ISBN:9781595936547
            DOI:10.1145/1242572

            Copyright © 2007 ACM

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            Publication History

            • Published: 8 May 2007

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