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Journal Articles International Journal of Reasoning-based Intelligent Systems Year : 2013

Corruption risk analysis using semi-supervised naïve Bayes classifiers

Abstract

In this paper, we consider the application of a naïve Bayes model for the evaluation of corruption risk associated 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 the detection of corruption in government transactions, and assisting audit agencies in becoming more proactive regarding corruption detection and prevention.
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hal-01058580 , version 1 (27-08-2014)

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Remis Balaniuk, Pierre Bessière, Emmanuel Mazer, Paulo Cobbe. Corruption risk analysis using semi-supervised naïve Bayes classifiers. International Journal of Reasoning-based Intelligent Systems, 2013, 5 (4), pp.237-245. ⟨10.1504/IJRIS.2013.058768⟩. ⟨hal-01058580⟩
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