%0 Journal Article
%T Suborbicular cluster recognition algorithm based on multi-dimensional analysis<br>基于多维度映射的类圆簇识别算法
%A XIAO Sheng-sheng
%A LIU Peng
%A <br>肖升生
%A 刘鹏
%J 计算机应用研究
%D 2011
%I 
%X In order to explore the real features of outcome clusters, this paper proposed a suborbicular cluster recognition algorithm based on multi-dimensional analysis. Firstly, it analyzed the given data sets in each dimension, then drew the frequency cure of every dimension and compared the characteristics of those cures. Finally, it identified the suborbicular cluster from a number of clusters. A large number of experiments show that the algorithm is robust, effective. It can be extended to high-dimensional data sets.
%K cluster recognition
%K analysis of data dimension
%K cluster analysis
%K data mining<br>聚类簇识别
%K 维度分析
%K 聚类分析
%K 数据挖掘
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=1F8EB868F38CE072BB1D34C4D1C3CDCB&yid=9377ED8094509821&vid=D3E34374A0D77D7F&iid=F3090AE9B60B7ED1&sid=03231C22C458E648&eid=61AB3EAD975F153B&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=16