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This method uses the theme model to express each song as the probability of belonging to several hidden themes, then models the user\u2019s behavior as multidimensional time series, and analyzes the series so as to better predict the use of music users\u2019 behavior preference and give reasonable recommendations. Then, a music recommendation method is proposed, which integrates the long\u2010term, medium\u2010term, and real\u2010time behaviors of users and considers the dynamic adjustment of the influence weight of the three behaviors so as to further improve the effect of music recommendation by adopting the advanced long short time memory (LSTM) technology. 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