Please use this identifier to cite or link to this item: https://hdl.handle.net/11147/9817
Title: A roadmap for semantifying recommender systems using preference management
Authors: Tapucu, Dilek
Tekbacak, Fatih
Ünalır, Murat Osman
Kasap, Seda
Keywords: Ontology
Recommender System
User Preference
Issue Date: 2010
Publisher: Springer Verlag
Abstract: The 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.
URI: https://doi.org/10.1007/978-90-481-9794-1_20
https://hdl.handle.net/9817
ISBN: 9.79E+12
ISSN: 1876-1100
Appears in Collections:Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

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