A Hybrid Intelligent Music Recommendation Model Based on Attention Mechanism and IndRNN

Abstract

The recommendation accuracy of traditional music recommendation algorithms is low. To solve this problem, a hybrid music recommendation algorithm based on attention mechanism and independently recurrent neural network (IndRNN) was proposed. Specifically, attention mechanism was introduced into the traditional IndRNN structure to solve the problem of traditional information overload, so as to improve the accuracy and efficiency of recommendation. The results showed that compared with the traditional LSTM algorithm and AINRNN algorithm, the accuracy of the proposed hybrid recommendation algorithm can reach 67.8%, and the normalized discounted cumulative gain (NDCG) is 58.1%, which shows that the proposed algorithm can improve the recommendation accuracy and has certain effectiveness in the field of traditional music recommendation.