Abstract
Traveling and city sightseeing are, in most cases, activities that involve small groups of users. Hence, a content personalization process, in a travel domain, requires taking into account simultaneously the preferences of different users. Moreover, a group recommendation system should also capture the possible intra-group relationships, which are fundamental features in a group decision process. In this paper, we model this problem as a multi-agent aggregation of preferences by using weighted social choice functions. In this context, weights can be extracted by analyzing the interactions of the group’s members on Online Social Networks.
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Rossi, S., Caso, A., Barile, F. (2015). Combining Users and Items Rankings for Group Decision Support. In: Bajo, J., et al. Trends in Practical Applications of Agents, Multi-Agent Systems and Sustainability. Advances in Intelligent Systems and Computing, vol 372. Springer, Cham. https://doi.org/10.1007/978-3-319-19629-9_17
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DOI: https://doi.org/10.1007/978-3-319-19629-9_17
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-19628-2
Online ISBN: 978-3-319-19629-9
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