Fuzzy ontologies-based user profiles applied to enhance e-learning activities
Nowadays, the impact of technological developments on improving human activities is becoming more evident. In e-learning, this situation is no different. There are common to use systems that assist the daily activities of students and teachers. Typically, e-learning recommender systems are focused on students; however, teachers can also benefit from these type of tools. A recommender system can propose actions and resources that facilitate teaching activities like structuring learning strategies. In any case, a complete users representation is required. This paper shows how a fuzzy ontology can be used to represent user profiles into a recommender engine and enhances the users activities into e-learning environments. A fuzzy ontology is an extension of domain ontologies for solving the problems of uncertainty in sharing and reusing knowledge on the Semantic Web. The user profile is built from learning objects published by the user himself into a learning object repository. The initial experiment confirms that the automatically obtained fuzzy ontology is a good representation of the users preferences. The experiment results also indicate that the presented approach is useful and warrants further research in recommending and retrieval information.
fuzzy ontology user profile recommendation learning object