Research on Optimizing the Curriculum System of College Students’ Innovation and Entrepreneurship Education under the Perspective of Internet Plus

This paper designs an online education course recommendation system based on collaborative filtering technology, and applies it to innovation and entrepreneurship education to further optimize the curriculum system of innovation and entrepreneurship education for college students under the background of “Internet +”. Aiming at the cold start problem and data sparsity of collaborative filtering recommendation models, the study utilizes genetic algorithms and K-means clustering algorithms to optimize the collaborative filtering algorithm. The research results show that the recommendation accuracy of the personalized recommendation model designed in this paper is 90% when the number of nearest neighbors is 30. The performance values of entrepreneurial attitude and entrepreneurial self-efficacy of the senior students of School Z were significantly improved (p<0.05) after teaching according to the innovative entrepreneurship education curriculum system designed in this paper. It shows that the entrepreneurship education content system designed in this paper can well recommend course resources for students and promote the reform of the curriculum system.