%0 Journal Article
%T Review of Outlier Detection<br>离群数据挖掘综述
%A HUANG Hong-yu
%A LIN Jia-xiang
%A CHEN Chong-cheng
%A FAN Ming-hui
%A <br>黄洪宇
%A 林甲祥
%A 陈崇成
%A 樊明辉
%J 计算机应用研究
%D 2006
%I 
%X This paper compared and analyzed major outlier detection algorithms. Their features were summarized to help users choose, study and improve algorithm for outlier detection. Attention was paid to high-dimensional data and spatial data because of their unique data structures as better and efficient algorithm is needed to deal with these types of data.
%K Data Mining
%K Outliers Detection
%K Exception
%K High-Dimension Outliers<br>数据挖掘
%K 离群检测
%K 异常
%K 高维离群
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=7B151F9F4DE5E8C8&yid=37904DC365DD7266&vid=EA389574707BDED3&iid=5D311CA918CA9A03&sid=5D311CA918CA9A03&eid=FC0714F8D2EB605D&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=14&reference_num=67