Analysis of Spatial Structure Distribution of Sports Culture Based on Chorography Big Data

Rezumat

The in-depth examination of sports culture's spatial distribution characteristics helps preserve diversity and enhance the transmission and development of regional sports culture. Few academics have studied the spatial distribution of sports culture, and none have exploited chorography big data. To address the void, this paper attempts to improve the spatial distribution structure of sports culture using big data from chorography. Based on chorography big data, the spatial distribution characteristics of sports culture were investigated. Next, the Canopy clustering algorithm and the k-means clustering algorithm were coupled to create the Cartesian k-means (CK-means) clustering algorithm for the concentration areas of sports culture. Unlike the k-means clustering technique, the suggested algorithm does not randomly select anomalous or edge sites as cluster centers, avoiding the local optimum trap. In addition, the algorithm's flow was described. The experimental findings suggest that our algorithm is superior.