Personalized recommendation method of Ideological and political course resources based on user model

摘要

Ideological and political courses play an important role in helping students establish correct three views. To help students better accept ideological and political education and learn ideological and political courses, a personalized recommendation method for ideological and political course resources based on user models is proposed. The research is divided into four parts. First, use network sniffing to obtain user browsing behavior records, then obtain user behavior characteristics and user learning styles from the records, and finally use collaborative recommendation algorithms to calculate similarity and nearest neighbors to realize ideological and political curriculum resources Personalized recommendation. The simulation experiment results show that compared with the four traditional recommendation methods, using the researched recommendation algorithm for personalized recommendation of ideological and political curriculum resources, the recommendation accuracy and recommendation coverage are higher, indicating that the researched recommendation algorithm has better performance, More conducive to serving students to learn ideological and political courses.