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dc.contributor.authorTsoukiàs, Alexis
dc.contributor.authorMatsatsinis, Nikolaos
dc.contributor.authorLakiotaki, Kleanthi
dc.date.accessioned2010-09-14T08:29:53Z
dc.date.available2010-09-14T08:29:53Z
dc.date.issued2011
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/4770
dc.language.isoenen
dc.subjectPreference Modelingen
dc.subjectUser Modeling and Clusteringen
dc.subjectRecommender Systemsen
dc.subjectMultiple Criteria Decision Analysisen
dc.subjectDisaggregation – Aggregation approachen
dc.subjectCollaborative Filteringen
dc.subject.ddc003en
dc.titleMulti-Criteria User Modeling in Recommender Systemsen
dc.typeArticle accepté pour publication ou publié
dc.description.abstractenRecommender systems are software applications that attempt to reduce information overload. Their goal is to recommend items of interest to the end users based on their preferences. To achieve that, most Recommender Systems exploit the Collaborative Filtering approach. In parallel, Multiple Criteria Decision Analysis (MCDA) is a well established field of Decision Science that aims at analyzing and modeling decision maker’s value system, in order to support him/her in the decision making process. In this work, a hybrid framework that incorporates techniques from the field of MCDA, together with the Collaborative Filtering approach, is analyzed. The proposed methodology improves the performance of simple Multi-rating Recommender Systems as a result of two main causes; the creation of groups of user profiles prior to the application of Collaborative Filtering algorithm and the fact that these profiles are the result of a user modeling process, which is based on individual user’s value system and exploits Multiple Criteria Decision Analysis techniques. Experiments in real user data prove the aforementioned statement.en
dc.relation.isversionofjnlnameIEEE Intelligent Systems
dc.relation.isversionofjnlvol26
dc.relation.isversionofjnlissue2
dc.relation.isversionofjnldate2011
dc.relation.isversionofjnlpages64-76
dc.relation.isversionofdoihttp://dx.doi.org/10.1109/MIS.2011.33
dc.description.sponsorshipprivateouien
dc.relation.isversionofjnlpublisherIEEEen
dc.subject.ddclabelRecherche opérationnelleen


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