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A Clustering Analysis Method for Massive Music Data


 
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1. Title Title of document A Clustering Analysis Method for Massive Music Data
 
2. Creator Author's name, affiliation, country Xu Yanping; School of Information Engineering, Yancheng Institute of Technology; China
 
2. Creator Author's name, affiliation, country Xu Sen; School of Information Engineering, Yancheng Institute of Technology; China
 
3. Subject Discipline(s)
 
3. Subject Keyword(s) Spectral clustering algorithm; K-mean; Music similarity; Audio period extraction
 
4. Description Abstract

Clustering analysis plays a very important role in the field of data mining, image segmentation and pattern recognition. The method of cluster analysis is introduced to analyze NetEYun music data. In addition, different types of music data are clustered to find the commonness among the same kind of music. A music data-oriented clustering analysis method is proposed: Firstly, the audio beat period is calculated by reading the audio file data, and the emotional features of the audio are extracted; Secondly, the audio beat period is calculated by Fourier transform. Finally, a clustering algorithm is designed to obtain the clustering results of music data.

 
5. Publisher Organizing agency, location Synergy Publishing Pte. Ltd.
 
6. Contributor Sponsor(s)
 
7. Date (YYYY-MM-DD) 2021-05-06
 
8. Type Status & genre Peer-reviewed Article
 
8. Type Type
 
9. Format File format PDF
 
10. Identifier Uniform Resource Identifier https://ojs.s-p.sg/index.php/met/article/view/6763
 
10. Identifier Digital Object Identifier (DOI) http://dx.doi.org/10.26549/met.v5i1.6763
 
11. Source Title; vol., no. (year) Modern Electronic Technology; 5 Vol, 1 No (2021)
 
12. Language English=en en
 
13. Relation Supp. Files
 
14. Coverage Geo-spatial location, chronological period, research sample (gender, age, etc.)
 
15. Rights Copyright and permissions Copyright © 2021 yanping xu
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