Integrating Tags and Ratings into User Profiling for Personalized Search in Collaborative Tagging Systems

Recently, some systems allow users to rate and annotate resources, e.g., MovieLens, and we consider that it provides a way to identify favor tags and annoying tags of a user by integrating user's rating and tags. In this paper, we reveal and elaborate on the limitations of current works on user profiling for personalized search in collaborative tagging systems. Then we propose a new multi-level user profiling model by integrating tags and ratings to achieve personalized search, which can reflect not only the user's favor but also a user's nuisances. To the best of our knowledge, this is the first effort to integrate the ratings and tags to model multi-level user profiles for personalized search.