Author(s)

Yu Fan ¹, Yuxin Chen ¹, Jinrong Yao ¹, Zhanchen Li ¹, Zhangliang Song ¹

Affiliation(s)

¹ College of Port, Coastal and Offshore engineering, Hohai University, Nanjing 210098, Jiangsu

Corresponding Author

Yu Fan

ABSTRACT

From the beginning, music is a part of human society and an important part of cultural heritage. As part of an effort to understand the role of music in the collective human experience, we attempted to develop a way to quantify the evolution of music.We have developed a comprehensive evaluation model to evaluate the influence of music.We mainly take "the number of followers of a genre" and "the number of influencers" as the quantitative evaluation index of music influence.We establish cosine similarity model to measure music similarity. After data normalization, we can conclude that the music similarity of artists from different schools is greater than that between different schools.

KEYWORDS

Music influence, directional network, cluster analysis

CITE THIS PAPER

Yu Fan, Yuxin Chen, Jinrong Yao, Zhanchen Li, Zhangliang Song. Evolution and revolutionary trend of artists and schools based on cluster analysis. Art and Performance Letters (2021) 2: 15-22. DOI: http://dx.doi.org/10.23977/artpl.2021.020503.

REFERENCES

[1] Jia Bo. Reflections on Charles Rosen's "musical significance" thesis [J]. Qilu art garden, 2020 (06): 14-20.
[2] Mendes A, Mauricio Archanjo Nunes Coelho, Neto R F. A Music Classification Model based on Metric Learning Applied to MP3 Audio Files [J]. Expert Systems with Applications, 2019.
[3] Wang Hailong, Liulin, Lin Min, Pei Dongmei. Recommendation algorithm for music Personalization Based on MIR and K-means label clustering [J/OL]. Journal of Jilin. University (Engineering Edition): 1-7 [2021-02-07].
[4] Buda, Andrzej; Jarynowski, Andrzej (December 2010).Life time of correlations and its applications. Wydawnictwo Niezalezne. pp. 5-21.ISBN9788391527290.

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