%0 Journal Article
%T A subspace clustering algorithm for high dimensional spatial data<br>一种高维空间数据的子空间聚类算法
%A WANG Sheng-sheng
%A LIU Da-you
%A CAO Bin
%A LIU Jie
%A <br>王生生
%A 刘大有
%A 曹斌
%A 等
%J 计算机应用
%D 2005
%I 
%X Traditional grid clustering methods fail to consider the affect of neighbored grids, and may result in unsmoothed clustering, wrong judgement of clustering boundary, etc. A subspace clustering algorithm for high dimensional spatial data was proposed, which added the affect of neighbored grids when clustering. Experiment results show that this algorithm conquers the unsmoothed clustering and deals with clustering boundary well.
%K grid clustering
%K high dimensional spatial clustering
%K spatial data mining<br>网格聚类
%K 高维空间聚类
%K 空间数据挖掘
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=831E194C147C78FAAFCC50BC7ADD1732&aid=946C7A6A2B2DAB7B&yid=2DD7160C83D0ACED&vid=C5154311167311FE&iid=708DD6B15D2464E8&sid=12303F3260BBCB69&eid=3D37452F59967074&journal_id=1001-9081&journal_name=计算机应用&referenced_num=6&reference_num=7