Proposed intelligent e-learning system using semantic web

E-learning is becoming an important tool in education. Hence, more and more education institutions use it. However, most of the e-learing systems used in most education institutions are the passive ones. Passive here means that they cannot adapt to users´ need or in other words they cannot personalize its users and provide only what users need accordingly. In order the system to be usefull to the users, it must be able to personalize them. One form of personalization in intelligent e-learning is the ability to recommend learning materials that fit to their needs. Such feature is called recommender. This paper proposes an intelligent recommender system using Semantic Web which is able to recommend learning materials to users based on their interest. To guide the users in learning and understand fully on a specific topic, a subject network, which is a relationship among subject, is used. The subject network will be presented in a list that suggests the order of learning.