基于相似度的離群模式發(fā)現(xiàn)模型
發(fā)布時間：2019-04-10 10:39
【摘要】：提出了基于相似度的離群模式發(fā)現(xiàn)模型 ,該模型主要利用知識屬性集分析離群點 ,既能夠處理離群點的數(shù)值屬性 ,又能夠處理其類別屬性 ;通過組間相似度從中發(fā)現(xiàn)離群模式 ,不僅回避離群點數(shù)量少的缺陷 ,還利用了離群點的隱含語義 .給出了在銀行結售匯交易數(shù)據(jù)上進行的實驗分析結果 ,模型發(fā)現(xiàn)了某地區(qū)的 3個可疑模式 ,該結果為金融犯罪分析提供有利線索 ;利用不同子空間角色劃分 ,可以發(fā)現(xiàn)個人、地區(qū)等不同對象間的異常資金流動 ;模式發(fā)現(xiàn)算法具有線性時間復雜度 ,在實際應用中具有較好的性能 .結果表明模型能檢測出可疑資金流動序列 ,為反洗錢工作提供有意義的線索 .
[Abstract]:An outlier pattern discovery model based on similarity is proposed. The model is mainly used to analyze the outliers by using the knowledge attribute set, which can not only deal with the numerical properties of the outliers, but also can handle the class attributes of the outliers, and find the outliers through the similarity among the groups. It not only avoids the defects of the number of outliers, but also uses the hidden semantics of the outliers. The result of the experimental analysis on the transaction data of the bank settlement is given. The model has found three suspicious patterns in a certain area. The result provides an advantageous clue for the analysis of the financial crime, and can find the individual by using the different sub-space characters. The pattern discovery algorithm has a linear time complexity and has better performance in practical application. The results show that the model can detect the flow sequence of suspicious funds and provide meaningful clues to the work of anti-money laundering.
【作者單位】： 華中科技大學計算機科學與技術學院 華中科技大學計算機科學與技術學院
【基金】：國家“十五”重大科技專項基金資助項目 (2 0 0 1BA10 2A0 6 11) .
【分類號】：D917
本文編號：2455732
[Abstract]:An outlier pattern discovery model based on similarity is proposed. The model is mainly used to analyze the outliers by using the knowledge attribute set, which can not only deal with the numerical properties of the outliers, but also can handle the class attributes of the outliers, and find the outliers through the similarity among the groups. It not only avoids the defects of the number of outliers, but also uses the hidden semantics of the outliers. The result of the experimental analysis on the transaction data of the bank settlement is given. The model has found three suspicious patterns in a certain area. The result provides an advantageous clue for the analysis of the financial crime, and can find the individual by using the different sub-space characters. The pattern discovery algorithm has a linear time complexity and has better performance in practical application. The results show that the model can detect the flow sequence of suspicious funds and provide meaningful clues to the work of anti-money laundering.
【作者單位】： 華中科技大學計算機科學與技術學院 華中科技大學計算機科學與技術學院
【基金】：國家“十五”重大科技專項基金資助項目 (2 0 0 1BA10 2A0 6 11) .
【分類號】：D917
【相似文獻】
相關重要報紙文章 前3條
1 趙士峰 ;離群眾近些,再近些[N];人民公安報·交通安全周刊;2005年
2 孫莉莉 李平偉;辦事公道了 離群眾近了[N];法制日報;2003年
3 郭冬青;建路管路為民富 一片朝陽鋪坦途[N];遼寧日報;2003年
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