Research on Personalized Ideological and Political Education Content Distribution System Based on Intelligent Algorithms

The creation of a personalized ideological and political education resource suggestion system has significant practical implications for boosting the efficiency of ideological and political education. Many challenges are preventing ideological and political education from progressing smoothly in the online environment, and the mainstream values of education are being affected as an effect. The educational model is reversed, there is a single way to communicate, and the educational content is solidified. It constructs a personalized recommendation user model for educational resources, and then builds a recommendation collaborative filtering algorithm using Data Mining (DM), that produces personalized suggestion of ideological and political education resources, improving the Collaborative Filtering Algorithm (CFA) allows for personalized recommendations of teaching materials for ideological and political education. As a result, DM-CFA has become a tool for education professionals can gain a better understanding of the learning and life characteristics of current college students through the collaborative operate of ideological and political education entities in the network environment, that likewise offers a diverse range of educational materials and varieties. As a result of the curriculum’s ideological function in mounding students’ brains, the ruling class’s history, gender, religion and nationality develop in society. Developing various learning channels for pupils can increase their interest for ideological and political research and help students grow holistically.