Abstract
The user’s search history includes some latent semantics that can be used to improve the user’s interests representation. In this paper we present a personalized information retrieval approach that highlights and use this latent semantics. This semantics, which we call personal semantics, is expressed by the different co-occurrence relationships between relevant terms, according to the different user’s search contexts. This personal semantics is integrated in a geo-social user profile for giving it more representativeness of the user interests. Then, to improve the search results relevance, the user profile is used to reformulate the user query for broadening the search scope without going further than the user needs.
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