A Survey of Recommender Systems: Approaches and Limitations

Abstract

Recommendation as a social process plays an important role in many applications as WWW has created the universe as a global village, with an explosive growth of enormous information. The paper presents an overview of the field of recommender systems along with the description of various approaches that are being used for generating recommendations. Recommendation techniques can be classified in to three major categories: Collaborative Filtering, Content Based and Hybrid Recommendations. The paper elaborates these approaches and discusses their limitations by describing the major problems suffered by recommendation methods. From basic techniques to the state-of-the-art, we attempt to present a comprehensive survey for recommendation techniques, which can be served as a roadmap for research and practice in this area.