Open AccessDesign and Implementation of Adaptive Recommendation System
Author(s) -
MagedEla zony,
Ahmed R. Khalifa,
Sayed Nouh,
Mohamed Hussein
Publication year - 2018
Publication title -
international journal of management, technology, and social science
Language(s) - English
Resource type - Journals
ISSN - 2581-6012
DOI - 10.47992/ijmts.2581.6012.0039
Subject(s) - computer science , relevance (law) , adaptive learning , learning object , semantic web , similarity (geometry) , multimedia , world wide web , personalized learning , interactive learning , information retrieval , human–computer interaction , artificial intelligence , open learning , teaching method , cooperative learning , mathematics education , mathematics , political science , law , image (mathematics)
E-learning offers advantages for E-learners by making access to learning objects at any time or place, very fast, just-in-time and relevance. However, with the rapid increase of learning objects and it is syntactically structured it will be time-consuming to find contents they really need to study.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 learning contents to the learner in flexible, interactive, and adaptive way. The semantic and recommendation and personalized search of Learning objects is based on the comparison of the learner profile and learning objects to determine a more suitable relationship between learning objects and learner profiles. Therefore, it will advise the e-learner with most suitable learning objects using the semantic similarity.