%0 Journal Article
%T Outlier detection algorithm based on shared nearest neighbor<br>基于共享最近邻的离群检测算法
%A SU Xiao-ke
%A ZHENG Yuan-pan
%A WAN Ren-xia
%A <br>苏晓珂
%A 郑远攀
%A 万仁霞
%J 计算机应用研究
%D 2012
%I 
%X This paper introduced an outlier detection algorithm based on the shared nearest neighbor clustering in order to detect the outliers with the mixed attributes. The algorithm calculated the shared nearest neighbor similarity measure between result clusters caused by the incremental clustering. It could not only find the arbitrary shape clusters but also identify the global outlier in large and high-dimensional dataset with different density. Presented approach had nearly linear time complexity with the number of attributes and the size of dataset which results in good scalability.
%K 共享最近邻
%K 离群检测
%K 任意形状簇
%K 混合属性
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=31780116840884783D9E4D1C8F7F1ADD&yid=99E9153A83D4CB11&vid=771469D9D58C34FF&iid=DF92D298D3FF1E6E&sid=BC035D350257EF96&eid=72D6EEA314C942FA&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=10