Background music adaptive recommendation method based on LDA-MURE model
Different emotional states of users require different background music,so an adaptive background music recommendation method based on LDA-MURE model is proposed.The audio features and social tags of background music are extracted,the features of the above data are fused by Fisher linear discriminant a-nalysis method,and the intra-class dispersion and inter-class dispersion of different types of background music are obtained by combining with the projection transformation method.The rhythm cycle changes of human emotions are analyzed through modern psychology,based on which the user's current emotional state is judged.Finally,the LDA-MURE model is constructed based on the LDA model to recommend dif-ferent types of background music for users.The experiment results show that the proposed method has low MEA index value,high P@N index value and high user satisfaction.
LDA-MURE modelFisher linear discriminant analysis methodfeature extractionback-ground music recommendationemotional state
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