基于LSTM模型的音乐推荐系统研究

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中文摘要：随着音乐推荐技术的快速发展,如何提升音乐推荐系统的准确性和用户满意度成为研究的重点.研究一种结合梅尔频率倒谱系数(Mel-Frequency Cepstral Coefficients,MFCC)、长短期记忆(Long Short-Term Memory,LSTM)网络、内容推荐方法的音乐推荐系统,并通过MATLAB平台进行测试.结果表明,该推荐系统表现良好.

外文标题：Research on Music Recommendation System Based on LSTM Model

外文摘要：With the rapid development of music recommendation technology,how to improve the accuracy and user satisfaction of music recommendation system has become the focus of research. A music recommendation system combining Mel-Frequency Cepstral Coefficients (MFCC),Long Short-Term Memory (LSTM) network and content recommendation method is studied. The test was carried out by MATLAB platform. The results show that the recommendation system performs well.

外文关键词：

music recommendationMel-Frequency Cepstral Coefficients (MFCC)Long Short-Term Memory (LSTM)content recommendation

作者：

范凯燕、胡彦红

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作者单位：

郑州科技学院,河南郑州 450000

关键词：

音乐推荐梅尔频率倒谱系数(MFCC) 长短期记忆(LSTM) 内容推荐

出版年：

2024

DOI：