Integration and optimization of higher mathematics teaching resources based on collaborative filtering algorithm

Nan Zhao

doi:10.1117/12.2672643

28 March 2023 Integration and optimization of higher mathematics teaching resources based on collaborative filtering algorithm

Nan Zhao

Author Affiliations +

Proceedings Volume 12597, Second International Conference on Statistics, Applied Mathematics, and Computing Science (CSAMCS 2022); 125973X (2023) https://doi.org/10.1117/12.2672643
Event: Second International Conference on Statistics, Applied Mathematics, and Computing Science (CSAMCS 2022), 2022, Nanjing, China

Abstract

As a basic subject in cuniversities, advanced mathematics education has become more and more important, and with the rapid improvement of message technique, the application of message technique in advanced mathematics education has become a general trend. The traditional higher mathematics education methods are outdated, the education efficiency is low, and the graphics display effect is not ideal. With the improvement of science and technique and the advent of the modern electrical age, education methods need to advance with the times. It is particularly important to explore a education method that can organically combine the traditional mathematics education mode with modern message technique, unify the practicability and feasibility of education and education, which can not only facilitate teachers' education but also help students to improve their learning effects. This paper is based on the collaborative filtering algorithm. In the personalized recommendation system, more core is the recommendation algorithm. Collaborative filtering is the most familiar and widely used recommendation algorithm.

Citation Download Citation

Nan Zhao "Integration and optimization of higher mathematics teaching resources based on collaborative filtering algorithm", Proc. SPIE 12597, Second International Conference on Statistics, Applied Mathematics, and Computing Science (CSAMCS 2022), 125973X (28 March 2023); https://doi.org/10.1117/12.2672643

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