RECOMMENDER SYSTEMS: A FRAMEWORK AND RESEARCH ISSUES

Advances in IT development make it possible for us to access virtually all kinds of information everyday. However this also brings the problem of “information overload”. Recommendation system is one of the solutions for information overload and it has been attracting more and more attentions recently. This paper reviews different approaches to recommender systems, mainly focused on collaborative filtering and content filtering approaches, and develops a general framework for recommender systems. We also discuss main research challenges and issues in the field of recommender systems in three areas: algorithm, human computer interaction (HCI), and social impacts.