%0 Journal Article
%T Subspace clustering method for high dimensional data stream<br>一种适用于高维数据流的子空间聚类方法
%A YAN Xiao-long
%A SHEN Hong
%A <br>沈鸿
%A 颜晓龙
%J 计算机应用
%D 2007
%I 
%X Inspired by the FP algorithm used in mining frequent patterns and the idea used in CLIQUE which is a classical method for clustering static data,a new data structure named dense grid-tree(DG-tree for short) was proposed to record the synopsis of the data streams for clustering.Then the clustering problem was transformed to the problem of constructing a DG-tree and searching for dense grid cells in the DG-tree.With the help of DG-tree,the subspace containing clusters was found.Experimental results show that this method has good cluster quality.
%K data mining
%K high dimension
%K data streams
%K subspace
%K clustering
%K FP-tree<br>数据挖掘
%K 高维
%K 数据流
%K 子空间
%K 聚类
%K FP树
%K 数据流
%K 空间聚类方法
%K data
%K stream
%K high
%K method
%K clustering
%K 伸缩性
%K 聚类效果
%K 实验
%K 过程
%K 网格单元
%K 高密
%K 搜索树
%K 利用
%K 构造
%K 转化
%K 聚类问题
%K 高维空间
%K 子空间
%K 存在
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=831E194C147C78FAAFCC50BC7ADD1732&aid=14E16CBD274305128F9074A6CA68EFF3&yid=A732AF04DDA03BB3&vid=DB817633AA4F79B9&iid=DF92D298D3FF1E6E&sid=BCF7BCA77FA8F9BA&eid=FE397BCF5D340F6F&journal_id=1001-9081&journal_name=计算机应用&referenced_num=1&reference_num=13