Integrating and Ranking Interests From User Profiles

Many websites allow their users to personalize their profiles. As users subscribe to many personalization websites, such as social net- works or search systems, each user owns different profiles, which are seldom compatible. Yet, there is a strong need for comparing the profiles of different users to discover shared interests, e.g., by integrating all user profiles into a global one. In this paper, we propose a novel method for in- tegrating and ranking user interests from various profiles. Our approach relies on the identification of high-level concepts around which similar user interests are clustered. We compute the weight of each cluster with respect to the other ones, thus enabling the ranking of the most shared user interests between user profiles.