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A personalised recommendation method of pop music based on machine learning

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成果类型:
期刊论文
作者:
Honghao Yu
作者机构:
[Honghao Yu] School of Music, Hunan City University, Yiyang 413000, China
语种:
英文
关键词:
machine learning;Word2Vec;LSTM network;popular music;personalised recommendation
期刊:
International Journal of Reasoning-based Intelligent Systems
ISSN:
1755-0556
年:
2023
卷:
15
期:
2
页码:
120-127
机构署名:
本校为第一机构
院系归属:
艺术学院
摘要:
In order to enhance the satisfaction of pop music personalised recommendation and improve the accuracy and efficiency of pop music personalised recommendation, a pop music personalised recommendation method based on machine learning is proposed. Firstly, the relevant theories of machine learning and short-term and long-term memory artificial neural networks are studied, and then the popular music word vector is extracted by using softmax function, and the collaborative filtering algorithm with weighting factor is introduced to calculate the similarity of popular music word vector. Finally, bas...

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