A fast clustering method based on multi-splitting grid

Clustering algorithms based on Grid are attractive for the task of data partition in spatial database. In the background of big data more and more research focuses on how to solve the conflict between efficiency and accuracy of clustering. Existing Grid-based clustering algorithms generally have a high time efficiency without considering the distribution of the data inside a grid. In this paper, a new clustering method based on multi-splitting grid (CBMG) is proposed. In CBMG algorithm grids are further split into cells in order to discover the data distribution in each grid. So if the data in a grid belongs to different clusters, CBMG can easily handle it. Because the number of cells in a grid is limited, CBMG can greatly improve the accuracy of clustering and only take less extra time consuming. Experiments show the better performance of CBMG.