A recommendation algorithm based on collaborative filtering technology in distance learning

Online learning resources growth speed is in geometric series with the rapid development of computer and communication technology. Users in distance learning and training process encounter the problems of information loss and resource overload, the main reason is that the distance learning system can't effectively understanding of teaching resources semantic information, different structure of teaching resources can't effectively organized into useful knowledge at present. In addition, the system can't provide personalized learning services for users according to different learning needs and backgrounds. How to quickly and effectively obtain the personalized learning information and learning resources from a large number of learning resources has become an urgent need for users. The CFR algorithm using combined similarity of user attributes and interest topics is proposed. Because of the problem of sparse matrix and cold start and in personalized recommendation, the paper proposes a CFR algorithm with combined similarity of user attributes and interest topics, and through experiment verify the algorithm validity.