Multidimensional Analysis of Music Education System Based on Multi-Intelligent Recommendation

Abstract

To better realize music education and improve the accuracy of music recommendation, a multidimensional analysis method of the music education system based on multi-intelligent recommendation is proposed. In the process of using this method to recommend music to users, the music characteristics are extracted and the music data are obtained from MIDI music, and three collaborative filtering algorithms are jointly used, namely user-based, content-based, and model-based collaborative filtering algorithms. The simulation results show that the proposed method can provide users with an intelligent music recommendation scheme according to the user's basic information and operation information. Compared with a single user-based recommendation or content-based, model-based recommendation, the proposed method has a certain degree of novelty and accuracy. Here, the recommendation accuracy rate can reach 94.8%, which is higher than the other two recommendation algorithms, showing certain advantages.