Abstract

Current search technologies work in "one size fits all" fashion. Therefore, the answer to a query is independent of specific user information need. In this paper, we describe a novel ranking technique for personalized search services that combines content-based and community-based evidences. The community-based information is used in order to provide context for queries and is influenced by the current interaction of the user with the service. Our algorithm is evaluated using data derived from...

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community