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dc.contributor.authorTapucu, D.
dc.contributor.authorTekbacak, F.
dc.contributor.authorÜnalir, M.O.
dc.contributor.authorKasap, S.
dc.date.accessioned2021-02-12T18:43:47Z
dc.date.available2021-02-12T18:43:47Z
dc.date.issued2010
dc.identifier.isbn9789048197934
dc.identifier.issn1876-1100
dc.identifier.urihttps://doi.org/10.1007/978-90-481-9794-1_20
dc.identifier.urihttps://hdl.handle.net/11147/9738
dc.description25th International Symposium on Computer and Information Sciences, ISCIS 2010en_US
dc.description.abstractThe work developed in this paper presents an innovative solution in the field of recommender systems. Our aim is to create integration architecture for improving recommendation effectiveness that obtains user preferences found implicitly in domain knowledge. This approach is divided into four steps. The first step is based on semantifying domain knowledge. In this step, domain ontology will be analyzed. The second step is to define an innovative hybrid recommendation algorithm based upon collaborative filtering and content filtering. The third step is based on preference modeling approach. And in the fourth step preference model and recommendation algorithm will be integrated. Finally, this work will be realized on Netflix movie data source. © 2011 Springer Science+Business Media B.V.en_US
dc.language.isoengen_US
dc.relation.isversionof10.1007/978-90-481-9794-1_20en_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectOntologyen_US
dc.subjectRecommender Systemen_US
dc.subjectUser Preferenceen_US
dc.titleA roadmap for semantifying recommender systems using preference managementen_US
dc.typeconferenceObjecten_US
dc.typeconferenceObjecten_US
dc.relation.journalLecture Notes in Electrical Engineeringen_US
dc.contributor.departmentIzmir Isntitute of Technologyen_US
dc.identifier.volume62 LNEEen_US
dc.identifier.startpage101en_US
dc.identifier.endpage104en_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US


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