Context-aware Recommender Systems J.UCS Special Issue
Katrien Verbert, Erik Duval, Stefanie Lindstaedt, Denis Gillet · 2010
Recommender systems have been researched and deployed extensively over the last decade in various application areas, including e-commerce, technology enhanced learning, e-health, adaptive multimedia and knowledge management. The three approaches of recommender systems commonly implemented are collaborative filtering, content-based filtering and hybrid filtering which combines aspects of both approaches [Balabanovic, 97]. Content-based recommender systems match content resources to user interests, typically specified in a user profile. Collaborative recommender systems recognize commonalities between users on the basis of their ratings, and generate new recommendations based on inter-user comparisons. Hybrid recommending approaches combine both content and user based similarity measures in recommendation algorithms.