Research on the Elective System with Personalized Recommendation Based on Collaborative Filtering

Problems of lacking in individualized curriculum recommendations and inefficiency exist in current course selection systems of institutions of higher education. In allusion to these limitations, this paper presents a novel collaborative filtering algorithm based on the project, user and attribute-value matrix through analysis and study of personalized recommendation technology. The proposed algorithm has been successfully applied to the elective system.Experimental results indicate that the proposed approach can solve cold-start technology in personalized recommendation algorithm, improve the related indicators significantly, and achieve a personalized recommendation and new courses recommendation.