Aggregating user preferences in group recommender systems: A crowdsourcing approach

dc.authorid0000-0002-6680-7291tr
dc.contributor.authorFirat Ismailoglu
dc.date.accessioned2023-06-23T05:33:09Z
dc.date.available2023-06-23T05:33:09Z
dc.date.issued2022tr
dc.departmentMühendislik Fakültesitr
dc.description.abstractWe present that group recommendations are similar to crowdsourcing, where the responses of different crowd workers are aggregated in the absence of ground truth. With this in mind, we mimic the use of the EM algorithm as in crowdsourcing to aggregate the preferences of group members to estimate group ratings and the expertise levels the group members. Moreover, for the first time in the literature, we cast the problem of estimating group rating as an ordinal classification problem relying on the natural ordering between the ratings, which allows us to define the expertise levels of the members in terms of sensitivity and specificity. In fact, we impose priors on the sensitivity and the specificity scores corresponding to the members, taking a Bayesian approach. We validate the effectiveness of the proposed aggregation method using the CAMRa2011 dataset, which consists of small and established groups, and the MovieLens dataset, which consists of large and random groups.tr
dc.identifier.doi10.1016/j.dss.2021.113663en_US
dc.identifier.issue113663tr
dc.identifier.scopus2-s2.0-85113941510en_US
dc.identifier.scopusqualityN/A
dc.identifier.urihttps://www.sciencedirect.com/science/article/abs/pii/S0167923621001731
dc.identifier.urihttps://hdl.handle.net/20.500.12418/14028
dc.identifier.volume152tr
dc.identifier.wosWOS:000721384600003en_US
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherElseviertr
dc.relation.ispartofDecision Support Systemsen_US
dc.relation.publicationcategoryUluslararası Hakemli Dergide Makale - Kurum Öğretim Elemanıtr
dc.rightsinfo:eu-repo/semantics/restrictedAccesstr
dc.subjectRecommender Systemstr
dc.subjectGroup Recommendationtr
dc.subjectCrowdsourcingtr
dc.titleAggregating user preferences in group recommender systems: A crowdsourcing approachen_US
dc.title.alternativeAggregating user preferences in group recommender systems: A crowdsourcing approachen_US
dc.typeArticleen_US

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