%0 Journal Article
%T FDBSCAN: A Fast DBSCAN Algorithm<br>FDBSCAN:一种快速 DBSCAN算法(英文)
%A ZHOU Shui geng
%A ZHOU Ao ying
%A JIN Wen
%A FAN Ye
%A QIAN Wei ning
%A <br>周水庚
%A 周傲英
%A 金文
%A 范晔
%A 钱卫宁
%J 软件学报
%D 2000
%I 
%X Clustering is an important application area for many fields including data mining, statistical data analysis, pattern recognition, image processing, and other business applications. Up to now, many algorithms for clustering have been developed. Contributed from the database research community, DBSCAN algorithm is an outstanding representative of clustering algorithms for its good performance in clustering spatial data. Relying on a density based notion of clusters, DBSCAN is designed to discover clusters of arbitrary shape.It requires only one input parameter and supports the user in determining an appropriate value of it.In this paper,a fast DBSCAN algorithm (FDBSCAN) is developed which considerably speeds up the original DBSCAN algorithm.Unlike DBSCAN,FDBSCAN uses only a small number of representative points in a core point's neighborhood as seeds to expand the cluster such that the execution frequency of region query and consequently the I/O cost are reduced.Experimental results show that FDBSCAN is effective and efficient in clustering large-scale databases,and it is faster than the original DBSCAN algorithm by several times.
%K Large scale database
%K data mining
%K clustering
%K fast DBSCAN algorithm
%K representative point<br>大规模数据库
%K 数据挖掘
%K 聚类
%K 快速DBSCAN算法
%K 代表点
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=7735F413D429542E610B3D6AC0D5EC59&aid=056D169A03EBC442C97A3F196078F7DE&yid=9806D0D4EAA9BED3&vid=708DD6B15D2464E8&iid=B31275AF3241DB2D&sid=B60458D1AE87BCD1&eid=195767709E606C85&journal_id=1000-9825&journal_name=软件学报&referenced_num=18&reference_num=20