Computer Engineering / Bilgisayar Mühendisliği
Permanent URI for this collectionhttps://hdl.handle.net/11147/10
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Conference Object A Roadmap for Semantifying Recommender Systems Using Preference Management(Springer, 2010) Tapucu, Dilek; Tekbacak, Fatih; Ünalır, Murat Osman; Kasap, SedaThe 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.Conference Object Citation - Scopus: 5Metamodeling Approach To Preference Management in the Semantic Web(Association for the Advancement of Artificial Intelligence, 2008) Tapucu, Dilek; Can, Özgü; Bursa, Okan; Ünalır, Murat OsmanPreference is a superiority state to determine the preferable or the superior of one entity, property or constraint to another from a specified selection set. Preference issue is heavily studied in Semantic Web research area. The existing preference management approaches only consider the importance of concepts for capturing users' interests. This paper presents a metamodeling approach to preference management. Preference meta model consists of concepts and semantic relations to represent users' interests. Users may have the same type preferences in different domains. Thus, metamodeling must be used to define similar preferences for interoperability in different domains. In this paper, preference meta model defines a general storage structure to manage different types of preferences for personalized applications. Copyright © 2008, Association for the Advancement of Artificial Intelligence.Conference Object Citation - Scopus: 3An Extension of Ontology Based Databases To Handle Preferences(INSTICC, 2009) Tapucu, Dilek; Ait-Ameur, Yamine; Jean, Stephane; Ünalır, Murat OsmanOntologies have been defined to make explicit the semantics of data. With the emergence of the SemanticWeb, the amount of ontological data (or instances) available has increased. To manage such data, Ontology Based DataBases (OBDBs), that store ontologies and their instance data in the same repository have been proposed. These databases are associated with exploitation languages supporting description, querying, etc. on both ontologies and data. However, usually queries return a big amount of data that may be sorted in order to find the relevant ones. Moreover, in the current, few approaches considering user preferences when querying have been developed. Yet this problem is fundamental for many applications especially in the e-commerce domain. In this paper, we first propose an extension of an existing OBDB, called OntoDB through extension of their ontology model in order to support semantic description of preferences. Secondly, an extension of an ontology based query language, called OntoQL defined on OntoDB for querying ontological data with preferences is presented. Finally, an implementation of the proposed extensions are described.