Creating an Advanced Web Based Environment using Semantic Web

Abstract

E-learning systems are of no help to the users if there are no powerful search engines and browsing tools to assist them. Most of the current web-based learning systems are closed systems where the courses and the learning material are fixed. The only thing that is dynamic is that the organization of the learning content is adapted to allow individualized learning environment. The learners of web-based e-learning systems belong to different categories based on their skills, background, preferences and learning styles. This paper focuses on personalized semantic search and recommending learning content that are appropriate to the learning environment. The semantic and personalized search of the learning content is based on comparison of the learner profile. The learner profile depends on re individual learning style of the user and learning objects’ metadata. This concept needs to be represented both in the learner profile as well as learning object description as certain data structures. Personalized recommendation of learning objects uses an approach to determine a more suitable relationship between learning objects and learning profiles. Thus, it may advise a learner with most suitable learning objects. Semantic learning objects search is based on the query expansion of the user query and by using the semantic similarity to retrieve semantic matched learning objects.