| 一种高效异常检测方法 |
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| 引用本文： | 蒋盛益,姜灵敏.一种高效异常检测方法[J].计算机工程,2007,33(7):166-168. |
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| 作者姓名： | 蒋盛益 姜灵敏 |
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| 作者单位： | 1. 广东外语外贸大学信息学院,广州,510420;中山大学广东省信息安全技术重点实验室,广州,510275
2. 广东外语外贸大学信息学院,广州,510420 |
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| 基金项目： | 国家自然科学基金
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广东外语外贸大学基金重点项目 |
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| 摘 要： | 借鉴万有引力思想提出了一种差异性度量方法和度量类偏离程度的方法，以此为基础提出了一种基于聚类的异常检测方法。该异常检测方法关于数据集大小和属性个数具有近似线性时间复杂度，适合于大规模数据集。理论分析以及在真实数据集上的实验结果表明，该方法是有效的，稳健并且实用。
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| 关 键 词： | 聚类 异常因子 异常检测 |
| 文章编号： | 1000-3428（2007）07-0166-03 |
| 修稿时间： | 2006-05-09 |
Approach of Efficient Outlier Detection |
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| JIANG Shengyi,JIANG Lingmin.Approach of Efficient Outlier Detection[J].Computer Engineering,2007,33(7):166-168. |
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| Authors: | JIANG Shengyi JIANG Lingmin |
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| Affiliation: | 1. School of Information, Guangdong University of Foreign Studies, Guangzhou 510420; 2. Guangdong Province Key Laboratory of Information Security, Sun Yat-sen University, Guangzhou 510275 |
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| Abstract: | Based on the idea of the law of gravity, the method measuring dissimilarity and the method measuring a cluster departure from the whole are presented. Based on these, an outlier detection approach based on clustering, named EOD, is introduced. The time complexity of the detection approach is nearly linear with the size of dataset and the number of attributes, which results in good scalability and adapts to large dataset. The theoretic analysis and the experimental results on real datasets show that the approach is effective, robust and practicable. |
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| Keywords: | Clustering Outlier factor Outlier detection |
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