Novel User Modeling Approaches for Personalized Learning Environments
Küçük Resim Yok
Tarih
2016
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
World Scientific Publ Co Pte Ltd
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Modeling 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.
Açıklama
Anahtar Kelimeler
Knowledge modeling, fuzzy distance metric, fuzzy k-nearest neighbor, artificial bee colony, adaptive artificial neural network
Kaynak
International Journal of Information Technology & Decision Making
WoS Q Değeri
Q2
Scopus Q Değeri
Cilt
15
Sayı
3
