%0 Journal Article
%T An Agglomerative Hierarchical Clustering Algorithm Based on Weighted Representative Points<br>一种基于加权多代表点的层次聚类算法
%A NI Wei-Jian
%A HUANG Ya-Lou
%A LI Fei
%A LIU Shang College of Software
%A Nankai University
%A Tianjin College of Information Technical Science
%A Nankai University
%A Tianjin
%A <br>倪维健
%A 黄亚楼
%A 李飞
%A 刘赏
%J 计算机科学
%D 2005
%I 
%X As an agglomerative hierarchical clustering algorithm, CURE firstly employs the method of representing clusters by selecting some "representative points". Through the analysis of the feature of traditional hierarchical clus- tering algorithm, a novel agglomerative hierarchical clustering algorithm called WRPC is proposed in this paper. WR- PC can identify clusters with complex shapes and avrious size by introducing the influence-weight-based representative points selection mechanism and k-nearest-neighbor-method-based clusters nesting mechanim. Experimental results show that WRPC can provide better clustering result with high executing efficiency.
%K Hierarchical clustering
%K Representative points
%K k-nearest neighbor graph
%K Data mining<br>层次聚类
%K 代表点
%K k-近邻图
%K 数据挖掘
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=64A12D73428C8B8DBFB978D04DFEB3C1&aid=B80A65AE43F31611&yid=2DD7160C83D0ACED&vid=9971A5E270697F23&iid=94C357A881DFC066&sid=2DBBF45CC176713E&eid=E2546871E5B846EF&journal_id=1002-137X&journal_name=计算机科学&referenced_num=0&reference_num=8