Personalized Learning Resources Recommendation Model Based on Transfer Learning

This paper based on the traditional learning resources of collaborative-filtering personalized recommendation systems exist sparse and cold start is put forward based on the personal learning resources study migration recommend model, study method can move from existing data transfer knowledge, to help the new knowledge in the future study. E-Learning environment, use of knowledge transfer for learners to provide the study resources recommended. And in a certain degree of collaborative-filtering solve sparse solution and cold start-up problem.