%0 Journal Article
%T Density of clustering algorithm based on relative distance<br>基于相对距离的密度聚类算法*
%A HE Xiao-jin
%A FU Yan
%A CHEN An-long
%A <br>何孝金
%A 傅彦
%A 陈安龙
%J 计算机应用研究
%D 2009
%I 
%X This paper firstly introduced the shortage of the traditional method in calculating the deficiencies in the application of clustering. To address this shortcoming, put forward a relative distance calculation method based on the weighted vector. The algorithm was based on the DBSCAN algorithm, and integrated of the calculation of relative distance and the application of the scope finding of the k-d tree. The algorithm can not only be good clustering effect, and the elimination of the unit of measurement data on the impact of cluster results.
%K relative distance
%K DBSCAN algorithm
%K k-d tree
%K clustering<br>相对距离
%K DBSCAN算法
%K 多维二进制搜索树
%K 聚类
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=81D2E97A55F68374F5FA240770C9A3FF&yid=DE12191FBD62783C&vid=96C778EE049EE47D&iid=E158A972A605785F&sid=65C780F1B91D7CD5&eid=530D9656D932F420&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=1&reference_num=8