Abstract: The challenge of the Semantic web technologies in the e-Learning domain can be identified with the arrangement of personalized encounters for the users. Especially, these applications can think about the individual necessities and prerequisites of learners. In this study, we propose a model for personalized e-Learning based on domain and aggregate usage profiles. The advantages of using this model, it presents an intelligent recommendation agent for personalized e-Learning course browsing. The main aim to use the technologies of semantics is to index information from various users usage and by providing with suggestions/recommendations based on the tracking data in one personalized search page.
J. Leo Immanuel and M. Vinay, 2017. Semantic Web Based Recommendation System for Efficient Learning. Asian Journal of Information Technology, 16: 95-99.