Samira Aouidi
ABSTRACT
E-learning systems have benefited greatly from the concepts of the social web and the emerging technologies of the web semantic (2.0). In this context; the research questions that arise are as follows: How to effectively use the learner's social network to derive information from his profile? How to benefit from this information (knowledge) to enrich his profile in the learning environment? How to exploit learners' knowledge for recommending educational resources in a human learning environment?
Our goal is to develop automatic learning environment. It is based on the semantic analysis of the social interactions that takes place between users-users and users-resources, the analysis is based on detecting communities of the semantic data that represents the users and their areas of interest. Further, it provides automatically the different recommendations with respect to the users interests, as well it proposes interactions with other users in the system. This system ensures that these recommendations will certainly improve the learning process by providing students with the best learning practices, the desirable collaborators, and the relevant resources that fit better their needs.
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