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Ideological and political exploration for some recommendation methods

Jianxi Zhao


I n the current wave of c urriculum ideological and political education in China, artifi cial intelligence course is an important
and frontier fi eld of ideological and political construction. Recommendation system is one of the core directions of artifi cial intelligence,
and recommendation system course has been widely off ered in numerous colleges and universities. This paper tries to integrate ideological
and political elements into some collaborative fi ltering m ethods based on users and items, fi ltering methods based on item attributes, and
recommendation methods based on classifi cation analysis and clustering analysis. The i deas/formulas/characteristics of the methods are
compared with some ideological and political contents, such that some abstract statistical analysis methods can be visualized, students can
be enlightened to understand the truth of life and work, and they can be helped to put up correct “Three Outlooks”.


recommendation system, recommendation methods, curriculum ideological and political education

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[1] Jinhua Wang, Guangmei Xu, Ning He, et al. Exploration and Practice of Integrating Ideological and Political Education into Postgraduate Curriculum

System -- A Case Study of Computer Vision Course [J]. Modernization of Education, 2019, 7(56): 131-134.

[2] Huagang Liang. Research on Ideological and Political Teaching Methods of “Machine Vision” Course [J]. Journal of Electrical and Electronic Teaching,

2021, 43(05): 112-115.

[3] Wei Li, Zhen Zhang. “Wisdom Enlightenment” and “Feelings Education” in the Course of “Pattern Recognition” [J]. Journal of Electrical and Electronic

Teaching, 2021, 43(03): 33-35+119.

[4] Yage Wang, Yong Liu, Mengli Du, et al. Exploration and Practice of Integrating Curriculum Ideolog ical and Political Education into the Teaching of

Machine Learning Course [ J]. Computer Knowledge and Technology, 2022, 18(33): 167-170.

[5] Lingling Wang, Deyi Xu. Research on Integrating I deological and Political Education into the Teaching of Data Mining and Machine Learning [J]. Modern

Vocational Education, 2022(10): 25-27.

[6] Xiaoxiao Hu. Teaching Cases of Deep Learning, into Which Integrating C urriculum Ideological and Political Education - Infi nite Series [J]. Mathematics

Learning and Research, 2023(3): 11-13.

[7] Yaqing Fang, Lina Zhu, Huimei Hu, et al. Exploration and Practice of Teaching Reform of Medical Information Retrieval and Utilization from the

Perspective of C urriculum Ideological and Political Education [J]. Chinese Journal of Medical Library and Information, 2022, 31(10): 75-80.

[8] Jian Liao, Suge Wang, Shan Qi. Mining and Practical Research on C urriculum Ideological and Political Elements of Natural Language Processing Course

for University Computers [J]. Heilongjiang Higher Education Research, 2022, 40(09): 156-160.

[9] Ying Zhang. Practice of Computer Curriculum Ideological and Political Teaching under the Mode of “One Core and Two Integration” -- Taking Graphics

and Image Processing C ourse as an Example [J]. Guangxi Education, 2022(29): 32-35.

[10] Lingying Pan, Jianjia He, Yijing Fan. Exploration of Curriculum Ideological and Political Teaching under the Background of New Engineering -- Taking

Artifi cial Intelligence and Intelligent Manufacturing Course as an Example [J]. Theoretical Research and Practice of Innovation and Entrepreneurship, 2019,

3(22): 55-56+59.

[11] Zhipeng Yang, Xuexue Liu. Design of Resource Personalized Recommendation System for Ideological and Political Theory Based on Data Mining [J].

Automation Technology and Applications, 2023, 42(01): 93-96.

[12] Fan Zhang, Guoquan Liu. Research on Recommendation System of University Ideological and Political Courses Based on Improved Collaborative

Filtering Algorithms [J]. Microcomputer Applications, 2019, 36(09): 1-4.

DOI: http://dx.doi.org/10.18686/modern-management-forum.v8i4.12387