| 海量信息异常检测问题的异常概率排序算法 |
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| 引用本文： | 陈刚,蔡远利,穆静,杨卫丽.海量信息异常检测问题的异常概率排序算法[J].西安交通大学学报,2011,45(4):36-40. |
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| 作者姓名： | 陈刚 蔡远利 穆静 杨卫丽 |
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| 作者单位： | 1. 西安交通大学电子与信息工程学院,710049,西安
2. 中国国防科技信息中心,100036,北京 |
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| 基金项目： | 国家自然科学基金资助项目(60972146,60602025) |
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| 摘 要： | 针对异常检测算法速度慢、精度低、稳定性差等问题,提出了一种通过异常概率排序提取异常点的算法(OAP).由于异常点相对正常点更容易通过对数据空间的均匀分割而孤立出来,所以OAP通过数据点在均匀N叉分割树中的孤立深度估算异常概率的大小,从而得到异常概率的排序,最终构造由k个异常概率最大的点组成的列表,列表中的数据就是所求的...
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| 关 键 词： | 数据挖掘 异常检测 均匀分割 异常概率排序 |
Ordinal Anomaly Probability Algorithm for Anomaly Detection Problems of Massive Data Sets |
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| CHEN Gang,CAI Yuanli,MU Jing,YANG Weili.Ordinal Anomaly Probability Algorithm for Anomaly Detection Problems of Massive Data Sets[J].Journal of Xi'an Jiaotong University,2011,45(4):36-40. |
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| Authors: | CHEN Gang CAI Yuanli MU Jing YANG Weili |
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| Institution: | 1.School of Electronics and Information Engineering,Xi′an Jiaotong University,Xi′an 710049,China; 2.National Defense Science & Technology Information Center,Beijing 100036,China) |
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| Abstract: | An ordinal anomaly probability method(OAP) is proposed to improve the efficiency,effectiveness and stability of existing anomaly detection algorithms.Since anomalies are easier to be isolated by uniformly partitioning the data space,the order of anomaly probabilities can be evaluated in terms of isolation depths in uniform N-ary partition trees.Then,the k largest probable anomalies are extracted.OAP can ignore the evaluation of distance and density,and hence reduces the complexity to O(n).Experimental resul... |
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| Keywords: | data mining anomaly detection uniform partition ordinal anomaly probability |
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