This paper provides an intelligent multiagent approach to incorporate human temperaments into the filtering process of an information recommendation service. Our approach is to de...
Recommender Systems are used in various domains to generate personalized information based on personal user data. The ability to preserve the privacy of all participants is an ess...
Collaborative filtering (CF) is valuable in e-commerce, and for direct recommendations for music, movies, news etc. But today's systems have several disadvantages, including ...
Context has been recognized as an important factor to consider in personalized Recommender Systems. However, most model-based Collaborative Filtering approaches such as Matrix Fac...
Recommender systems have been proposed to exploit the potential of social network by filtering the information and offer recommendations to a user that he is predicted to like. Co...