A Semantic Web Architecture for Context Recommendation System in E-learning Applications
Bouchra Bouihi, Mohamed Bahaj
Journal of E-Technology, Vol. 8, No. 4, 2017.
DOI: 
Link: http://www.dline.info/jet/fulltext/v8n4/jetv8n4_1.pdf
Abstract:
The widespread use of e-learning applications has put emphasis on the importance of having applications more
personalized and adaptable to every learner needs. The one size fits all is no more working. Every learner should be delivered
the right learning material that suits its learning context in the right time. The challenge is to incorporate the recommendation
system in e-learning platforms in order to offer to learners a successful learning experience. In response to this challenge, in
this paper, we propose semantic web architecture of a context recommendation system in e-learning by means of which the
learners will be offered learning content based on their profiles, activities and social interactions. The proposed architecture
is a re-engineering of classical web architecture of current e-learning platforms. Itâ€™s based on semantic web technologies. It
comprises ontology that guarantee a shareable and reusable modeling of the learning context and OWL Rules filtering that
will be used as recommendation technique.