Context-Aware User's Interests for Personalizing Mobile Search

In the past, most personalized retrieval models have been solely based on the computational behavior of the user to model the user profile. Personalized mobile search should however take the changing environment of the mobile user into account in order to better improve the search results quality. In this paper we propose an approach to personalize search results for mobile users by exploiting both cognitive and spatiotemporal context of the user. We propose to model the user on three semantic dimensions: time, location and interests. A case based reasoning approach is adopted to select the appropriate user profile for re-ranking the search results. In the absence of a standard evaluation framework for mobile search, we propose an evaluation scenario based on diary study entries. Our experiments undertaken in front of Yahoo boss search service1shows that our retrieval approach is effective.

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