TY  - JOUR
T1  - Semantic Web Based Recommendation System for Efficient Learning
AU - Immanuel, J. Leo AU - Vinay, M. 
JO  - Asian Journal of Information Technology
VL  - 16
IS  - 1
SP  - 95
EP  - 99
PY  - 2017
DA  - 2001/08/19
SN  - 1682-3915
DO  - ajit.2017.95.99
UR  - https://makhillpublications.co/view-article.php?doi=ajit.2017.95.99
KW  - Semantic web
KW  -e-Learning
KW  -personalized learning
KW  -ontologies
KW  -recommendations
AB  - 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 user’s usage and by providing with
suggestions/recommendations based on the tracking data in one personalized search page.
ER  -