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  4. Vol 2, Issue 5, 2021

Research on music influence based on TOPSIS Model

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DOI: 10.23977/artpl.2021.020508 | Downloads: 6 | Views: 763

Author(s)

Yanfeng Li 1

Affiliation(s)

1 College of Mathematics and Informatics, South China Agricultural University, Guangzhou 510642, China

Corresponding Author

Yanfeng Li

ABSTRACT

In this paper, based on the analysis of data using data mining technology, based on the evolution of music with events and the influence of artists, the following discussion is carried out. In this paper, a graph model based on TOPSIS comprehensive weight determination method is established. Based on entropy weight method and variation coefficient method, directed weight graph influence is established for the given data set_data.csvThe music influence parameters in the graph model are mined.On this basis, the music characteristics of artists are clustered within and between schools to measure the similarity of artists, showing the similarity and influence between schools and within schools; in addition, it analyzes how the style of schools changes with the passage of time.By comparing the average musical characteristics of influencers and followers, it is proved that some musical characteristics of influencers play a similar role in influencing the musical color of a particular artist.From the analysis of the changes of the total amount of music genres existing in each era with time, and the genres with better development trend or strong representativeness in each era, we can express the influence of music on time or environment, and understand the value of music through the Internet through the influence of visualization.

KEYWORDS

Entropy weight method, TOPSIS comprehensive weighting method, cluster analysis, time series

CITE THIS PAPER

Yanfeng Li. Research on music influence based on TOPSIS Model. Art and Performance Letters (2021) 2: 38-42. DOI: http://dx.doi.org/10.23977/artpl.2021.020508.

REFERENCES

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[2] Shih, H.S., shyur, H.J., Lee, E.S.: the extension of TOPSIS in group decision making.Mathematics and computer modeling 45801 – 813 (2007).
[3] Lopez, M.M., Heymann, e., senar, M.A.: dynamic heuristic analysis of workflow scheduling in grid system. Proceedings of the 5th IEEE International Symposium on parallel and distributed computing (2006).
[4] Kavyasrujana D., Rao B.C. used cosine similarity measure for hierarchical clustering of sentence extraction. (2015).

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