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A Symbolic Model-based Approach for Making Collaborative Group Recommendations

Sergio Queiroz 1 Francisco de Carvalho 
LIP6 - Laboratoire d'Informatique de Paris 6
Abstract : In recent years, recommender systems have achieved great success. Popular sites give thousands of recommendations every day. However, despite the fact that many activities are carried out in groups, like going to the theater with friends, these systems are focused on recommending items for sole users. This brings out the need for systems capable of performing recommendations for groups of people, a domain that has received little attention in the literature. In this article we introduce a novel method of making collaborative recommendations for groups, based on models built using techniques from symbolic data analysis. Finally, we empirically evaluate the proposed method to see its behaviour for groups of different sizes and degrees of homogeneity, and compare the achieved results with a baseline methodology.
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Submitted on : Thursday, April 6, 2017 - 5:33:44 PM
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Sergio Queiroz, Francisco de Carvalho. A Symbolic Model-based Approach for Making Collaborative Group Recommendations. 9th Meeting of the International Federation of Classification Societies (IFCS), Jul 2004, Chicago, United States. pp.361-370, ⟨10.1007/978-3-642-17103-1_35⟩. ⟨hal-01503229⟩



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