Personalized Queries under a Generalized User Profile Model based on Fuzzy SPARQL Preferences

With the abundance of information that is currently available on the Web, the way we model user preferences plays a key role for providing only relevant and personalized results. A lot of research attention has been dedicated to the integration of user preference profiles into queries in the relational database context. However, the same topic remains still under-investigated in the context of the Semantic Web. In this paper, we introduce a fuzzy RDF model for expressing fuzzy preferences forming user profile. Then, we propose a query personalization framework that enhances the initial query with the best user preferences retrieved from the user profile and then ranks the query results based on their degree of interest. Finally, we present some experimental results that show the feasibility of this new approach.