A Symbolic Model-Based Approach for Making Collaborative Group Recommendations

Abstract

In recent years, recommender systems have achieved greatsuccess. Popular sites give thousands of recommendations everyday. However, despite the fact that many activities are carriedout in groups, like going to the theater with friends, thesesystems are focused on recommending items for sole users. Thisbrings out the need for systems capable of performingrecommendations for groups of people, a domain that has receivedlittle attention in the literature. In this article we introduce anovel method of making collaborative recommendations for groups,based on models built using techniques from symbolic dataanalysis. Finally, we empirically evaluate the proposed method tosee its behaviour for groups of different sizes and degrees ofhomogeneity, and compare the achieved results with a baselinemethodology.