The LOF (local outlier factor) algorithm is a very distinguished local outlier detecting method, which assigns each object an outlier-degree value.

LOF算法是一个著名的局部离群点查找方法，该方法赋予了表征每一个空间点偏离程度的数值。

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The offset-based outlier mining detecting method is a key technique for analysis of outlier mining.

基于偏离的孤立点探测方法是孤立点分析一个重要的技术。

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The problem of outlier mining has been variously called outlier analysis, anomaly detection, exception mining, detecting rare events, mining rare classes, deviation detection, etc.

孤立点挖掘又称孤立点分析、异常检测、例外挖掘、小事件检测、挖掘极小类、偏差检测。

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Experimental results show that the presented algorithm is effective in detecting outliers in the outlier subsequences detection and can improve the effectiveness of the outlier subsequences detection.

实验结果表明，所提出的算法对异常子序列的异常检测具有很好的效果，能够有效地提高时间序列中异常子序列检测的效率。

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Experimental results show that the presented algorithm is effective in detecting outliers in the outlier subsequences detection and can improve the effectiveness of the outlier subsequences detection.

实验结果表明，所提出的算法对异常子序列的异常检测具有很好的效果，能够有效地提高时间序列中异常子序列检测的效率。

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