Ourdia Bouidghaghen

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General Web search engines characterized by "onesize fits all" provide the same results for the same keyword queries even though these latter are submitted by different users with different intentions. In mobile Web search, the expected results for some queries could vary depending upon the user'slocation. We believe that identifying user's geographic(More)
We introduce a novel situation-aware approach to personal-ize search results for mobile users. By providing a mobile user with appropriate information that dynamically satisfies his interests according to his situation, we tackle the problem of information overload. To build situation-aware user profile we rely on evidence issued from retrieval situations.(More)
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(More)
We discuss the issue of evaluating our context-based person-alized mobile search approach with a methodology based on a combination of two evaluation approaches: context simulation and user study. Our personalized approach aims at exploiting some context-aware user profiles through a per-sonalized score to re-rank initial search results obtained from a(More)
In the past, most personalized retrieval models have been solely based on the computational behavior of the user (visited URL, viewed documents) to model the user profile independently of his changing environment (time, location, near persons, etc). In this paper we propose an approach to personalize Web search results for mobile users by exploiting both(More)
The paper presents a preliminary investigation of potential methods for extracting semantic views of text contents, which go beyond standard statistical indexation. The aim is to build kinds of fuzzily weighted structured images of semantic contents. A preliminary step consists in identifying the different types of relations (is-a, part-of, related-to,(More)
In this poster, we propose to personalize the search results for mobile users by modeling the user on three semantic dimensions: time, location and interests. A case based reasoning approach (CBR) is adopted to select the appropriate user profile for re-ranking the search results. Our experiments show that our retrieval approach is effective.