A Local Outlier Detection Approach Based on Graph-Cut

摘要：

Most of local outlier detection methods proposed in the literature make use of k nearest neighbors. These methods suffer from a drawback that the detected results are sensitive to the parameter k. In this paper, a novel graph composed of two rounds of minimum spanning tree (MST) is presented. In terms of the two-round-MST based graph, we propose a graph-cut method to detect the local outliers. The experimental results on both synthetic and real datasets demonstrate that, compared with k nearest neighbors related local outlier detection methods, the proposed method can produce more robust results.

作者: Caiming Zhong Xueming Lin Ming Zhang

作者单位: College of Science and Technology Ningbo Univeristy, Ningbo, 315211, P.R.China

会议类型: 国际会议

会议名称: The Second International Joint Conference on Computational Science and Optimization(CSO 2009)(2009 国际计算科学与优化会议)

会议地点: 三亚

会议语种:英文

页码: 714-718

在线出版日期: 2009-04-24（万方平台首次上网日期，不代表论文的发表时间）