Combining users and items rankings for group decision support

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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 Advances in Intelligent Systems and Computing (Vol. 372, pp. 151–158). Springer Verlag. https://doi.org/10.1007/978-3-319-19629-9_17

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