Attentive Context-Aware Music Recommendation

Tao, Yu; Zhang, Yuanxing; Bian, Kaigui

doi:10.1109/dsc.2019.00017

Cited by 10 publications

(2 citation statements)

References 17 publications

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“…is purpose can be abstracted as a dichotomous mathematical problem [21]. A hybrid recommendation algorithm based on attention mechanism and independent recurrent neural network by RNN (AINRNN) is improved based on the deep learning neural network.…”

Section: Improved Music Recommendation Algorithm For Deep Neural Netw...mentioning

confidence: 99%

Improved Music Recommendation Algorithm for Deep Neural Network Based on Attention Mechanism

Xin

2022

Mobile Information Systems

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With the increasingly close combination of the Internet and people’s production and life, the total amount of global data and information also grows increasingly. In order to save users the time to find their favorite music among many music types, the music recommendation service arises at the historic moment and is widely concerned by scholars. Traditional music recommendation system based on the collaborative filtering algorithm has low recommendation accuracy, poor real-time performance, sparsity, system cold start, and so on. Moreover, the traditional music recommendation algorithm only simply uses user behavior characteristics and does not make good use of user history for listening to audio characteristics. In view of the above question, this section based on the attention mechanism of the deep neural network music recommendation algorithm, through the use of improved MFCC audio data preprocessing, the extracted audio combined with the user’s own portrait features, through the AIN RNN network recommended list, by learning user history listening to songs, improves the model-recommended accuracy.

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Section: Improved Music Recommendation Algorithm For Deep Neural Netw...mentioning

confidence: 99%

Improved Music Recommendation Algorithm for Deep Neural Network Based on Attention Mechanism

Xin

2022

Mobile Information Systems

View full text Add to dashboard Cite

show abstract

“…For Song [112], while psychologists can provide a deeper understanding of the theoretical background to emotion, computing researchers can provide valuable tools to help analyze data related to musical emotions. Furthermore, the need and potential to include context in music listening with the knowledge on musical emotions is acknowledged in both areas [10,92,53,1,116].…”

Section: Introductionmentioning

confidence: 99%