International Journal of Computer Networks and Communications Security (IJCNCS)
Learning is an active transaction between people as one person teaches and another learns. It is a shared experience because students explore new areas of knowledge together in such a way as to create a common core and concepts. In this paper, the authors propose an improved E-Learning social network exploiting approach based on clustering algorithm and graph model, which can automatically group distributed e-learners with similar interests and make proper recommendations, which can finally enhance the collaborative learning among similar e-learners. Through similarity discovery, trust weights update and potential friend's adjustment, the algorithm implements an automatic adapted trust relationship with gradually enhanced satisfactions.