Risk based Government Audit Planning using Naive Bayes Classifiers

机译：利用Naive Bayes分类器的基于风险的政府审计计划

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In this paper we consider the application of a naive Bayes model for the evaluation of fraud risk connected with government agencies. This model applies probabilistic classifiers to support a generic risk assessment model, allowing for more efficient and effective use of resources for fraud detection in government transactions, and assisting audit agencies in transitioning from reactive to proactive fraud detection model.

机译：在本文中，我们考虑在与政府机构相关的欺诈风险评估中的应用。该模型应用概率分类器来支持通用风险评估模型，允许更高效和有效地利用政府交易中的欺诈检测资源，并协助审计机构从反应到主动欺诈检测模型转换。

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《International Conference on Knowledge-Based and Intelligent Information and Engineering Systems》|2012年||共11页
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作者
Remis Balaniuk; Pierre Bessiere; Emmanuel Mazer; Paulo Cobbe;
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中图分类 TP18-53;
关键词
Data mining; Naive Bayes; Fraud detection;

机译：数据挖掘;天真的贝叶斯;欺诈检测;

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Risk based Government Audit Planning using Naive Bayes Classifiers

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