Novel User Modeling Approaches for Personalized Learning Environments

Basit Öğe Kaydı
dc.authoridCOLAK, ILHAMI/0000-0002-6405-5938
dc.authoridKAHRAMAN, Hamdi Tolga/0000-0001-9985-6324
dc.contributor.authorKahraman, H. Tolga
dc.contributor.authorSagiroglu, Seref
dc.contributor.authorColak, Ilhami
dc.date.accessioned2024-09-11T19:52:06Z
dc.date.available2024-09-11T19:52:06Z
dc.date.issued2016
dc.departmentİstanbul Gelişim Üniversitesien_US
dc.description.abstractModeling user knowledge and creating user profiles not only for special web-based social media but also for complex and mixed personalized learning environments are important research challenges. The key component for adaptation is the user's knowledge model. This paper introduces fuzzy metric (FM)-based novel and efficient similarity measurement method and adaptive artificial neural network (AANN) and artificial bee colony (ABC)-based knowledge classification approaches for personalized learning environments. For this purpose, FM-based method has been developed to measure distances more efficiently among the users and their knowledge model using the web logs/session data. In addition, a novel knowledge classifier based on ABC and AANN having combined with the generic object model has been developed for user modeling strategies and user modeling server of adaptive educational electric course (AEEC). Finally, the approaches have been tested to compare the classification performance of the user modeling methods developed for user modeling task. The experimental results have shown that proposed methods have improved similarity measurements considerably and decreased the misclassifications in user modeling processes. Thus, powerful user modeling approaches have been presented to the literature. It is expected that the approaches introduced in this article can be a reference to others researches and to develop more adaptive and personalized web applications in future.en_US
dc.identifier.doi10.1142/S0219622016500164
dc.identifier.endpage602en_US
dc.identifier.issn0219-6220
dc.identifier.issn1793-6845
dc.identifier.issue3en_US
dc.identifier.scopus2-s2.0-84964391228en_US
dc.identifier.startpage575en_US
dc.identifier.urihttps://doi.org/10.1142/S0219622016500164
dc.identifier.urihttps://hdl.handle.net/11363/7909
dc.identifier.volume15en_US
dc.identifier.wosWOS:000376866900004en_US
dc.identifier.wosqualityQ2en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.language.isoenen_US
dc.publisherWorld Scientific Publ Co Pte Ltden_US
dc.relation.ispartofInternational Journal of Information Technology & Decision Makingen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.snmz20240903_Gen_US
dc.subjectKnowledge modelingen_US
dc.subjectfuzzy distance metricen_US
dc.subjectfuzzy k-nearest neighboren_US
dc.subjectartificial bee colonyen_US
dc.subjectadaptive artificial neural networken_US
dc.titleNovel User Modeling Approaches for Personalized Learning Environmentsen_US
dc.typeArticleen_US

Dosyalar

Koleksiyon

WoS İndeksli Yayınlar Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu