Universidad Complutense de Madrid
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An Architecture and Functional Description to Integrate Social Behaviour Knowledge Into Group Recommender Systems

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Quijano Sánchez, Lara and Recio García, Juan Antonio and Díaz Agudo, Mª Belen (2014) An Architecture and Functional Description to Integrate Social Behaviour Knowledge Into Group Recommender Systems. Applied Intelligence, 40 (4). pp. 732-748. ISSN 1573-7497

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Official URL: htpp://dx.doi.org/10.1007/s10489-013-0504-y



Abstract

In this paper we consider the research challenges of generating a set of recommendations that will satisfy a group of users, with potentially competing
interests. We review di�erent ways of combining the preferences of di�erent users and propose an approach that takes into account the social behaviour within a
group. Our method, named delegation-based prediction method, includes an analysis of the group characteristics, such as size, structure, personality of its members in conict situations, and trust between group members. A key element in this paper is the use of social information available in the Web to make enhanced recommendations to groups. We propose a generic architecture named arise (Architecture for Recommendations Including Social Elements) and describe, as a case study, our Facebook application HappyMovie: a group recommender system that is designed to provide assistance to a group of friends that might be selecting which movie to watch on a cinema outing. We evaluate the performance (compared with the real group decision) of di�erent recommenders that use increasing levels of
social behaviour knowledge.


Item Type:Article
Uncontrolled Keywords:Group Recommender systems, Social Networks, Personality, Trust, Generic Architecture
Subjects:Sciences > Computer science
Sciences > Computer science > Artificial intelligence
ID Code:31221
Deposited On:01 Jul 2015 12:49
Last Modified:07 Jul 2015 11:30

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