A personalized recommendation method using a tagging ontology for a social e-learning system

Abstract

As collaborative tagging has become increasingly popular, its role in social e-learning systems has attracted much attention. In this paper, we present a method to provide personalized recommendation services using a tagging ontology for a social e-learning system called TagSES. The TagSES ontology models relationships among students, lecture materials and tags, and the tags are mapped to the domain ontology. Based on the reasoning rules, students with similar interests are clustered and relevant lecture materials are recommended. To validate our method, we have implemented a prototype social e-learning system for a music history domain. © 2011 Springer Berlin Heidelberg.