A study on the characteristics of historical evolution of vocal works based on data mining

Abstract

Data mining is able to discover the laws and fixed patterns of data in complex data, which has the advantages that traditional data analysis methods do not have, and has been applied to the analysis of musical works in a large number of applications. Firstly, the historical publication data of vocal works is organized, which is used to outline the historical evolution stages and trends of vocal works. The collected information on Chinese vocal works was analyzed with CiteSpace, and multiple vocal works were clustered into five categories based on the theme keywords, and 11 cluster labels were delineated on the basis of the word frequency results. The timeline mapping results show that the creation of Chinese vocal works can be categorised into three periods: the period of development, the period of prosperity, and the period of adjustment. Finally, based on the different periods, it can be summarized that the historical evolution of Chinese musical works is characterized by diversification of themes, singing styles, and musical styles.