Integrating and Ranking Interests From User Profiles!
نویسندگان
چکیده
Many websites allow their users to personalize their profiles. As users subscribe to many personalization websites, such as social networks 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 integrating 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.
منابع مشابه
Combining Learning and Word Sense Disambiguation for Intelligent User Profiling
Understanding user interests from text documents can provide support to personalized information recommendation services. Typically, these services automatically infer the user profile, a structured model of the user interests, from documents that were already deemed relevant by the user. Traditional keyword-based approaches are unable to capture the semantics of the user interests. This work p...
متن کاملA Personalized Approach for Re-ranking Search Results Using User Preferences
Web search engines provide users with a huge number of results for a submitted query. However, not all returned results are relevant to the user’s needs. Personalized search aims at solving this problem by modeling search interests of the user in a profile and exploiting it to improve the search process. One of the challenges in search personalization is how to properly model user’s search inte...
متن کاملMining Semantically Indexed Documents for Intelligent User Profiling
Typically, personalized information recommendation services automatically infer a user profile, a structured model of the user interests, from documents the user already deemed as relevant. Traditional keyword-based approaches are unable to capture the semantics of the user interests. This work proposes a strategy consisting of two steps. The first one is a semantic indexing procedure based on ...
متن کاملA personalized search using a semantic distance measure in a graph-based ranking model
The goal of search personalization is to tailor search results to individual users by taking into account their profiles, which include their particular interests and preferences. As these latter are multiple and changing over time, personalization becomes effective when the search process takes into account the current user interest. This paper presents a search personalization approach that m...
متن کاملImproving Ontology-Based User Profiles
Personalized Web browsing and search hope to provide Web information that matches a user’s personal interests and thus provide more effective and efficient information access. A key feature in developing successful personalized Web applications is to build user profiles that accurately represent a user’s interests. The main goal of this research is to investigate techniques that implicitly buil...
متن کامل