Novel clustering algorithm based on grid and density

In view of the efficiency and quality issues existed in both the grid and density clustering algorithms,this paper proposed the combination of density and grid clustering algorithm,that was DGCA(density and grid based clustering algorithm) which based on density and grid.The given algorithm firstly divided data space into grids;followed by storing data into the grid cell,and used DBSCAN to conduct clustering mining;finally,it carried on clustering merging and elimination of noise points,and maps the local clustering results to the global clustering results.The experiment is theoretically varified with artificial data set on this clustering algorithm,and shows that the algorithm gained enhance on both time efficiency and clustering quality.