Clustering method of unbalanced large data density based on dynamic grid

Article type: Research Article

Authors: Wang, Yang^{; *}

Affiliations: Business School, Huanggang Normal University, Huanggang 438000, China

Correspondence: [*] Corresponding author. E-mail: yonghou@mls.sinanet.com.

Abstract: In order to effectively ensure the clustering quality of unbalanced big data density, improve the clustering accuracy of unbalanced big data density and shorten the clustering time of unbalanced big data density, an unbalanced big data density clustering method based on dynamic grid is proposed. This paper analyzes the definition and characteristics of dynamic grid, and expounds the clustering method based on density and dynamic grid. Build a dynamic grid of unbalanced big data through unbalanced big data database. Consider a single spatial object, divide the unbalanced big data dynamic grid, and calculate the cell density of the unbalanced big data dynamic grid. Dynamic grid technology is adopted to realize unbalanced large data density clustering. Experimental results show that the proposed algorithm has good clustering effect, which can effectively improve the clustering accuracy of unbalanced big data and shorten the clustering time of unbalanced big data density.

Keywords: Dynamic grid, clustering method, spatial objects, unbalanced big data, density clustering

DOI: 10.3233/WEB-220021

Journal: Web Intelligence, vol. 20, no. 4, pp. 287-295, 2022