Personalized Intelligent Recommendation Model Based on Hybrid Collaborative Filtering Algorithm

Authors

  • Yujiao Wang College of Teacher Education, Kunming University, Kunming 650214, China
  • Haiyun Lin College of Physical Science and Technology, Kunming University, Kunming 650214, China
  • Lina She Science and Technology Management Department, Kunming University, Kunming 650214, China
  • Li Sun School of Information Engineering, Kunming University, Kunming 650214, China

Abstract

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

Cite As

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.



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Published

2022-11-01

Issue

Vol. 30 No. 6 (2022): International Journal of Engineering Intelligent Systems

Section

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