Intelligent Recommendation of Ideological and Political Course Content Based on the BPNN Algorithm Improved by Attention Mechanism

Abstract

This paper improved the back-propagation neural network (BPNN) algorithm for recommending ideological and political courses by a squeeze-and-excitation network (SEnet) and a multi-head attention mechanism. Simulation experiments were conducted to compare the improved algorithm with two other recommendation algorithms, followed by ablation experiments. Moreover, the effectiveness of the recommendation algorithm was tested in actual teaching of ideological and political courses. The results demonstrated that the improved BPNN algorithm outperformed others and the SEnet and the multi-head attention mechanism significantly enhanced the accuracy of recommendations. The algorithm effectively improved students’ performance in ideological and political courses and was satisfied by the majority of students.