A Kind of  Algorithms for Euclidean Distance-Based Outlier Mining and its Application to Expressway Toll Fraud Detection

Zhijun Huang, Chuangwen Xia
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引用次数: 6

Abstract

This  paper present the concept of the outlier mining, discussed using  Euclidean  distance-based outlier mining to analyse the expressway toll to anti-defrauding, for to illustrate it, gived the example of toll collection’s  man-day and  nullah, analysed the toll collection data in Microsoft SQL Server, helped the toll check man to find outlied data, via emphases check on those outlier data, can fing the evidence for anti-defrauding; can offer proofe chain  to treat with the defrauding things, this paper also analysed the strongpoint and the shortcoming of using the  algorithms  of  Euclidean distance-based outlier to analyse the defrauding in highway toll collection.
一种基于欧氏距离的离群点挖掘算法及其在高速公路收费欺诈检测中的应用
本文提出了离群值挖掘的概念,讨论了利用基于欧几里得距离的离群值挖掘来分析高速公路收费反欺诈,为了说明这一点,给出了收费的人日和水坑的例子,在Microsoft SQL Server中分析了收费数据,帮助收费员找到离群数据,通过对这些离群数据的重点检查,可以找到反欺诈的证据;能够提供证据链来处理欺诈行为,本文还分析了利用基于欧氏距离的离群点算法来分析高速公路收费欺诈行为的优点和不足。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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