基于决策树算法的洗钱交易识别研究被引量：9

Research on Money Laundering Recognition Based on Decision Tree Algorithm

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摘要通过对我国外汇洗钱活动特征的分析,将数据挖掘技术中的决策树分析方法与反洗钱领域知识相结合,选择适当的洗钱交易识别策略与方法,利用真实交易数据进行试验,从中发现有价值的洗钱犯罪规律。结果表明,该方法可有效提高洗钱交易行为的识别效率。 Money laundering behavior recognition was a process of knowledge discovery in databases(KDD).Data Mining was an important technique of KDD.In this paper,the characteristics of Chinese foreign exchange money laundering activities,and combine decision tree approach with financial domain knowledge were analyzed.The suitable money laundering transaction recognition strategy and method were chosen.By making full use of the real transaction data to carry on the experiment,useful rules of money laundering were dis...

作者张成虎赵小虎

机构地区西安交通大学经济与金融学院

出处《武汉理工大学学报》 CAS CSCD 北大核心 2008年第2期154-156,共3页 Journal of Wuhan University of Technology

基金国家自然科学基金(70771087) 西安交通大学“985工程”二期建设项目(07200701)

关键词洗钱交易知识发现数据挖掘决策树算法 money laundering knowledge discovery in databases（KDD） data mining decision tree algorithm

分类号 F832.6 [经济管理—金融学]

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