宋明秋

个人信息Personal Information

副教授

硕士生导师

主要任职:Associate Professor

其他任职:中国软件行业协会系统安全工程分会主任,国际注册信息安全专家CISSP,国际注册信息系统审计师CISA

性别:女

毕业院校:大连理工大学

学位:博士

所在单位:系统工程研究所

学科:管理科学与工程. 系统工程

办公地点:D526, Management Building,No.2 Linggong Road,Dalian China 116024

联系方式:songmq at dlut.edu.cn,

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Local Isolation Coefficient-Based Outlier Mining Algorithm

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论文类型:会议论文

发表时间:2009-07-25

收录刊物:EI、CPCI-S、Scopus

卷号:2

页面范围:448-451

关键字:data mining; outlier; local isolation coefficient

摘要:Outlier detection has received significant attention in many applications, such as detecting credit card fraud or network intrusions. Distance-based outlier detection is an important data mining technique that rinds abnormal data objects according to some distance function. However, when this technique is applied to datasets whose density distribution is different, usually the detection efficiency and result are not perfect. With analysis of features of outliers in datasets, as the improvement of Local Sparsity Coefficient-Based (LSC) Mining of Outliers, we rank each point on the basis of its distance to its kth nearest neighbor and the distribution of its k nearest neighborhood. A novel outlier detecting algorithm based Local Isolation Coefficient (LIC) is presented in this paper, which is shown better outlier mining results through the experiments.