Optimizing Preferences within Groups: A Case Study on Travel Recommendation

Authors:
Fabiana Lorenzi;Fernando Santos;Paulo R. Ferreira, Jr.;Ana L. Bazzan
Affiliations:
Instituto de Informática, UFRGS, Porto Alegre, Brazil 91.501-970 and Universidade Luterana do Brasil, Canoas, Brazil 8001;Instituto de Informática, UFRGS, Porto Alegre, Brazil 91.501-970;Instituto de Informática, UFRGS, Porto Alegre, Brazil 91.501-970 and Instituto de Ciências Exatas e Tecnológicas, Centro Universitário Feevale, Novo Hamburgo, Brasil RS239, 275 ...;Instituto de Informática, UFRGS, Porto Alegre, Brazil 91.501-970
Venue:
SBIA '08 Proceedings of the 19th Brazilian Symposium on Artificial Intelligence: Advances in Artificial Intelligence
Year:
2008

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Abstract

This work describes a multiagent recommender system where agents work on behalf of members of a group of customers, trying to reach the best recommendation for the whole group. The goal is to model the group recommendation as a distributed constraint optimization problem, taking customer preferences into account and searching for the best solution. Experimental results show that this approach can be sucessfully applied to propose recommendations to a group of users.