Title: Personalised recommendation method of educational resources for ideological and political courses based on data mining

Authors: Jun-Cheng Wang; Lin Zeng

Addresses: Science and Technology College, Nan Chang Hang Kong University, Nanchang, 332020, China ' Science and Technology College, Nan Chang Hang Kong University, Nanchang, 332020, China

Abstract: In order to improve the teaching quality of ideological and political courses, a personalised recommendation method of educational resources for ideological and political courses based on data mining is proposed in this paper. Firstly, the topological structure for course resources distribution is established, and the data structure features of educational resources are rearranged through sparse and discrete dimension detection. Then, a personalised recommendation model of educational resources is established to control and optimise the recommendation process of teaching resources. The knowledge map model is used to realise the information interaction between users and projects, and the entity embedding and high-order preference dissemination recommendation methods are used to realise the personalised recommendation of educational resources for ideological and political courses. The experimental results show that this method can contributes to high recommendation satisfaction and has a certain application value.

Keywords: data mining; ideological and political courses; educational resources; personalised recommendation; knowledge transfer.

DOI: 10.1504/IJRIS.2025.147451

International Journal of Reasoning-based Intelligent Systems, 2025 Vol.17 No.3, pp.193 - 199

Received: 03 Apr 2023
Accepted: 23 May 2023
Published online: 16 Jul 2025 *

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