%0 Journal Article
%T An improved density-based outlier mining algorithm<br>一种改进的基于密度的离群数据挖掘算法
%A CUI Guan-xun
%A ZHU Qing-sheng
%A <br>崔贯勋
%A 朱庆生
%J 计算机应用
%D 2007
%I 
%X Based on the characteristic that outliers are not included in the appointed neighborhood of inliers, an improved algorithm for outlier mining was proposed. Data was judged whether it was included in the appointed neighborhood of inliers firstly. If the answer was negative, the number of data that was included in the appointed neighborhood was counted. Experimental results show that the improved algorithm is effective and efficient in outlier mining and it is faster than the original algorithm.
%K data mining
%K outlier
%K density-based<br>数据挖掘
%K 离群数据
%K 基于密度
%K 改进
%K 基于密度
%K 离群数据
%K 挖掘算法
%K algorithm
%K outlier
%K mining
%K 速度
%K 数据集
%K 快速
%K 数据测试
%K 二维空间
%K 判断
%K 邻域
%K 利用
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=831E194C147C78FAAFCC50BC7ADD1732&aid=14E16CBD2743051265F0B6467601258D&yid=A732AF04DDA03BB3&vid=DB817633AA4F79B9&iid=38B194292C032A66&sid=8966A0F1B07BE5EE&eid=B4F9D541F855CF96&journal_id=1001-9081&journal_name=计算机应用&referenced_num=0&reference_num=10