Recommendation Technologies: Survey of Current Methods and Possible Extensions

Abstract

The paper presents a survey of the field of recommender systems and describes current recommendation methods that are usually classified into the following three main categories: content-based, collaborative, and hybrid recommendation approaches. The paper also describes various limitations of current recommendation methods and discusses possible extensions that can improve recommendation capabilities. These extensions include, among others, improvement of understanding of users and items, incorporation of the contextual information into the recommendation process, support for multi-criteria ratings, and provision of more flexible and less intrusive types of recommendations.