Personalized Intelligent Recommendation Model Based on Hybrid Collaborative Filtering Algorithm
In the context of a learning environment, the purposes of this paper are to construct an intelligent learning resource model based on personalized recommendation; improve the efficiency of the current recommendation algorithm; propose a hybrid collaborative filtering recommendation algorithm; establish a push strategy for intelligent learning resources; create a two-way matching mapping strategy; and promote a personalized and intelligent education service. It is anticipated that the realization of these goals will help to address several problems: the overall quality of the recommendation system, the new-user cold start recommendation, the slow convergence of the recommendation algorithm, the system stability and other issues.
Keywords: personalized learning, intelligent recommendation, resource model, recommendation algorithm
Y. Wang, H. Lin, L. She, L. Sun, "Personalized Intelligent Recommendation Model Based on Hybrid Collaborative
Filtering Algorithm", Engineering Intelligent Systems, vol. 30 no. 6, pp. 441-446, 2022.