关键词: 数据聚类, 基于网格, 基于密度, 混合算法

Abstract: Currently，existing grid based clustering algorithms are more efficient in time complexity，but the cluster quality is not satisfied，especially at the cluster boundaries.In this paper，the authors propose an efficient algorithm to solve this kind of problem，which broke the cells around the clusters’ boundaries and considered the data points in these cells to be processed，then the authors use a similarity function to assign them into the corresponding cells.Experimental evaluation shows that this method is more efficient than CLIQUE and has the time complexity within O（n）.

Key words: data clustering, grid-based, density-based, hybrid algorithm