PQR＊TDBSCAN改进算法

AN Improve Algorithm based PQR＊TDBSCAN

DBSCAN是基于密度的聚类算法的一个典型代表。但是DBSCAN算法在处理大规模数据库时，存在很大欠缺。PQR＊TDBSCAN是针对DBSCAN算法内存使用过大、I／O消耗过多等方面提出的，但是在实际应用中发现存在异常挂死的可能。本文针对PQR＊TDBSCAN的缺陷进行了改进。测试表明，本算法在处理海量数据过程中降低了DBSCAN对时间和空间的需求。

DBSCAN algorithm is an outstanding representative of density based on clustering algorithms. However, there are some defects when dealing with large-scale database. Aiming at requiring large volume of memory support and needing a lot of I/O costs, a PQR＊TDBSCAN algorithm is presented. But actually there is the possibility of making the algorithm goes to the abnormal status. In this paper, a PQR＊TDBSCAN improve algorithm is presented. Experimental results show that the new algorithm is superior to the original DBSCAN in efficiency.