Fuzzy Group Decision Making for Influence-Aware Recommendations

dc.cclicenceCC-BY-NC-NDen
dc.contributor.authorCapuano, Nicolaen
dc.contributor.authorChiclana, Franciscoen
dc.contributor.authorHerrera-Viedma, Enriqueen
dc.contributor.authorFujita, Hamidoen
dc.contributor.authorLoia, Vincenzoen
dc.date.acceptance2018-11-01en
dc.date.accessioned2018-11-21T10:05:20Z
dc.date.available2018-11-21T10:05:20Z
dc.date.issued2018-11-13
dc.descriptionThe file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.en
dc.description.abstractGroup Recommender Systems are special kinds of Recommender Systems aimed at suggesting items to groups rather than individuals taking into account, at the same time, the preferences of all (or the majority of) members. Most existing models build recommendations for a group by aggregating the preferences for their members without taking into account social aspects like user personality and interpersonal trust, which are capable of affecting the item selection process during interactions. To consider such important factors, we propose in this paper a novel approach to group recommendations based on fuzzy influence-aware models for Group Decision Making. The proposed model calculates the influence strength between group members from the available information on their interpersonal trust and personality traits (possibly estimated from social networks). The estimated influence network is then used to complete and evolve the preferences of group members, initially calculated with standard recommendation algorithms, toward a shared set of group recommendations, simulating in this way the effects of influence on opinion change during social interactions. The proposed model has been experimented and compared with related works.en
dc.funderFEDER financial support from the Project TIN2016en
dc.identifier.citationCapuano, N., Chiclana, F., Herrera-Viedma, E., Fujita, H., Loia, V. (2018) Fuzzy Group Decision Making for Influence-Aware Recommendations. Computers in Human Behavior, 101, pp. 371-379en
dc.identifier.doihttps://doi.org/10.1016/j.chb.2018.11.001
dc.identifier.issn0747-5632
dc.identifier.urihttp://hdl.handle.net/2086/17241
dc.language.isoenen
dc.projectid75850-Ren
dc.publisherElsevieren
dc.researchgroupInstitute of Artificial Intelligence (IAI)en
dc.researchinstituteInstitute of Artificial Intelligence (IAI)en
dc.subjectrecommender systemsen
dc.subjectgroup decision makingen
dc.subjectsocial influenceen
dc.titleFuzzy Group Decision Making for Influence-Aware Recommendationsen
dc.typeArticleen

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