Applied Mathematics and Nonlinear Sciences
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Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 10, Issue 1


Published
on

March 19, 2025


Pages


DOI

Article

Data Mining Techniques for the Preservation and Inheritance of Classical Vocal Music in Modern Society

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Authors

Xiaoqing Chi Affiliation:
Conservatory of Music, Henan University of Economics and Law, Zhengzhou, Henan, 450000, China.


Abstract

This study firstly describes the application of data mining technology in the protection and inheritance of classical vocal music, and secondly proposes the basic steps of association rule algorithms in data mining technology for exploring the association between classical vocal music and user collections. This study selects part of the data of a music platform, scientifically analyzes the relationship between user collection and classical vocal works, and empirically proves the classical vocal music protection and inheritance method based on data mining technology proposed in this paper. The study concludes that the probability of users collecting the Ninth Symphony and Carmen is 63.122%, and the probability of collecting the Ninth Symphony and then Carmen is 86.544% when the Ninth Symphony is collected. The experimental data is a strong evidence for the preservation and inheritance of classical vocal music in modern society.


Keywords

Data mining techniques, Association rules, Classical vocal music, Preservation and heritage, 03B70


Citation

Chi, X. (2025). Data mining techniques for the preservation and inheritance of classical vocal music in modern society. Applied Mathematics and Nonlinear Sciences, 10(1). https://doi.org/10.2478/amns-2025-0353

Published by: Engineering Journals

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