Authors: Mihaela Brut, Florence Sedes, Romulus Grigoras, Vincent Charvillat
Addresses: Faculty of Computer Science, 'A.I.Cuza' University of Iasi, 16 Berthelot str., 700483 Iasi, Romania. ' IRIT, Paul Sabatier University, 118 Route de Narbonne, 31062 Toulouse, Cedex 9, France. ' IRIT-ENSEEIHT, 6, allee Emile Monso, 31029 Toulouse, Cedex 4, France. ' IRIT-ENSEEIHT, 6, allee Emile Monso, 31029 Toulouse, Cedex 4, France
Abstract: This paper provides a service-oriented solution that explores the ontology-based modelling of users and documents in order to provide users with personalised recommendations of resources. Alongside the adoption of semantic web technologies for ontology-based modelling, our approach aims at a better relevance for recommendations by adopting a hybrid recommendation technique, combining a collaborative filtering and a content-based approach. The collaborative filtering module adopts a Markov Decision Process (MDP) in order to predict the next concept which will be focused on by the user, tracking the user navigation through an ontology instead of through the structure of a particular site. The content-based recommender module adopts a k nearest neighbours approach and exploits the similarities between the user and document modelling.
Keywords: personalised recommendation; multimedia; e-learning; ontology; electronic learning; online learning; resource recommendations; semantic web; modelling; collaborative filtering; content-based recommenders.
International Journal of Web and Grid Services, 2008 Vol.4 No.3, pp.314 - 329
Available online: 28 Nov 2008 *Full-text access for editors Access for subscribers Purchase this article Comment on this article