%0 Journal Article
%T Self-adapted clustering algorithm based on grid density<br>一种基于网格密度的自适应聚类分析算法*
%A DONG Yan
%A GE Jun-wei
%A <br>董琰
%A 葛君伟
%J 计算机应用研究
%D 2007
%I 
%X This paper presented a new efficient clustering algorithm that combined the approach based on density and grid. The most creativity of this novel algorithm was capturing the shape and extent of a cluster by using grid, and then analyzed the data based on the grid density. It also could reach high efficiency because of its linear time complexity. Both theory analysis and experimental results prove that this algorithm can discover clusters with arbitrary shape and is insensitive to noise data.
%K clustering
%K density
%K grid
%K connectivity<br>聚类
%K 密度
%K 网格
%K 连通性
%K 网格密度
%K 自适应
%K 聚类分析算法
%K density
%K grid
%K based
%K 显示
%K 测试
%K 性能比较
%K 实验
%K 识别率
%K 空间复杂性
%K 时间
%K 敏感
%K 噪声数据
%K 形状
%K 发现
%K 聚类算法
%K 基于网格
%K 基于密度
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=C793235A4E87B8F683236B7BCADB4EC6&yid=A732AF04DDA03BB3&vid=B91E8C6D6FE990DB&iid=5D311CA918CA9A03&sid=014B591DF029732F&eid=11B4E5CC8CDD3201&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=5