01934nas a2200253   4500000000100000008004100001653002500042653002900067653002500096653002200121653004300143653004500186653003400231653002300265653003200288653002500320100001500345700001400360700001800374245015100392856014800543300001200691520097700703       2024                            d10aCorrelation analysis10aData analysis techniques10aDescriptive analysis10aHeritage networks10aIntangible cultural heritage inheritor10aIntangible cultural heritage protections10aIntangible cultural heritages10aK-means clustering10aK-means clustering analysis10aK-means++ clustering1 aXueyi Yang1 aYiwen Pan1 aJinfeng Zhang00aConstruction of Intangible Cultural Heritage Inheritor Profiles Based on K-means Clustering Analysis and Recommendations for Protective Strategies  uhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85209129968&doi=10.1145%2f3695080.3695139&partnerID=40&md5=786b663177e91d37c02ed76cbffc6f15  a334-3413 aIn the era of big data, data analysis techniques can deeply mine and discover information hidden in massive and diverse datasets. Based on the information of 3,057 representative inheritors provided by the China Intangible Cultural Heritage Network, this paper first uses descriptive analysis to understand the basic distribution of inheritors in terms of gender, ethnicity, and region. Next, correlation analysis is employed to explore the relationships between these variables. On this basis, K-means clustering analysis is utilized to classify the inheritors, constructing a detailed profile of the intangible cultural heritage (ICH) inheritors. The study finds that female inheritors are relatively underrepresented in the field of ICH, and the distribution of intangible cultural heritage exhibits a strong regional characteristic. This research aims to provide scientific guidance for the development of local intangible cultural heritage and training of inheritors.