Information retrieval improvement in E-learning systems using semantic Web

Abstract EN

E-Learning and Web-based education and has become a very important branch of new educational technology.

In this paper we present information retrieval improvement in e-learning system using semantic web.

This paper focuses on design and implementation of adaptive recommendation e-learning system at the sea ports and use e-learning system and semantic web to deliver the learning objects to learners in an interactive, flexible and adaptive manner.

The purpose of this paperis to help trainer in port community to find not just Learning object but also the type of Learning object that they should appreciate from a lot of content and types based on their priority and needs, Our solution consists of a Recommendation System that provides recommendations to the E-learner and advise a learner with most suitable resources and learning objects based on semantic web technology using a hybrid technique of collaborative filtering and content-based filtering using Semantic web, We are also faced with the need to adapt the learning process to the progress of the e-learner, his preferences, as well as existing competencies, to ensure that the system is both effective and efficient, especially considering the multitude of learning objects in existence, we find that adaptive recommendation E-learning systems using semantic web will help the e-learner to find the information and learning object easily and relatively for their queries and interest.