Design and Implementation of Adaptive Recommendation System

Main Article Content

MagedElazony
Ahmed Khalifa
Sayed Nouh
Mohamed Hussein

Abstract

E-learning offers advantages for E-learners by making access to learning objects at any time orplace, very fast, just-in-time and relevance. However, with the rapid increase of learning objectsand it is syntactically structured it will be time-consuming to find contents they really need tostudy.In this paper, we design and implementation of knowledge-based industrial reusable,interactive web-based training and use semantic web based e-learning to deliver learningcontents to the learner in flexible, interactive, and adaptive way. The semantic andrecommendation and personalized search of Learning objects is based on the comparison of thelearner profile and learning objects to determine a more suitable relationship between learningobjects and learner profiles. Therefore, it will advise the e-learner with most suitable learningobjects using the semantic similarity.

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How to Cite
MagedElazony, Ahmed Khalifa, Sayed Nouh, & Mohamed Hussein. (2018). Design and Implementation of Adaptive Recommendation System. International Journal of Management, Technology and Social Sciences (IJMTS), 3(1), 101–117. Retrieved from https://supublication.com/index.php/ijmts/article/view/787
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