A Data-overlap-partitioning-based Parallel DBSCAN Algorithm
基于数据交叠分区的并行DBSCAN算法

As an outstanding representative of clustering algorithms,DBSCAN algorithm show good performance in spatial data clustering.However,for large spatial databases,original DBSCAN requires large volume of memory support and could incur substantial I/O costs.With the rapid development of high performance computer,especially appearance of the cluster computers give a means to overcome the defect of original DBSCAN algorithm.Experimental results show that the new algorithm is superior to the original DBSCAN in efficiency.