Toward a New Recommender System Based on Multi-criteria Hybrid Information Filtering

The Communities of Practice of E-learning (CoPEs) are virtual spaces that facilitate learning and acquisition of new knowledge for its members. To achieve these objectives CoPE members exchange and share learning resources that can be (online courses, URLs, articles, theses, etc ...). The growing number of adherents to the CoPE increases the number of learning resources inserted into the memory of this learning space. As consequence, access to relevant learning resource and collaboration between members who have similar needs become even more difficult. Therefore, recommender systems are required to facilitate such tasks. In this paper we propose a personalized recommendation approach dedicated to CoPE that we call Three Dimensions Hybrid Recommender System (3DHRS). The approach is hybrid as it uses collaborative filtering supported by content based filtering to eliminate the problems of cold start and new item. Furthermore, it considers three criteria namely role, interest and evaluation to efficiently solve the new user, and sparsity issues. A prototype of the proposed system has been implemented and evaluated through the use of Moodle platform as it hosts many communities of practice. Very promising results in terms of mean absolute error have been obtained.