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Volumn 3955 LNAI, Issue , 2006, Pages 538-542

Predicting fraudulent financial statements with machine learning techniques

Author keywords

[No Author keywords available]

Indexed keywords

DATA SET; DECISION TREES; FRAUDULENT FINANCIAL STATEMENTS (FFS);

EID: 33745873686     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11752912_63     Document Type: Conference Paper
Times cited : (13)

References (19)
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  • 3
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    • An empirical analysis of the likelihood of detecting fraud in New Zealand
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    • (2002) Managerial Auditing Journal , vol.17 , Issue.4 , pp. 192-204
    • Ansah, S.O.1    Moyes, G.D.2    Oyelere, P.B.3    Hay, D.4
  • 4
    • 3142730133 scopus 로고    scopus 로고
    • A decision aid for assessing the likelihood of fraudulent financial reporting
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    • (2000) Auditing: A Journal of Practice & Theory , vol.9 , Issue.1 , pp. 169-178
    • Bell, T.1    Carcello, J.2
  • 5
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    • A roadmap for future neural networks research in auditing and risk assessment
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    • Calderon, T.G.1    Cheh, J.J.2
  • 9
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    • Assessing the risk of management fraud through neuralnetwork technology
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    • (1997) Auditing: A Journal of Practice and Theory , vol.16 , Issue.1 , pp. 14-28
    • Green, B.P.1    Choi, J.H.2
  • 14
    • 0001171722 scopus 로고    scopus 로고
    • Using sparseness and analytic QP to speed training of support vector machines
    • M. S. Kearns, S. A. Solla, & D. A. Cohn (Eds.), MA: MIT Press
    • Platt, J. Using sparseness and analytic QP to speed training of support vector machines. In M. S. Kearns, S. A. Solla, & D. A. Cohn (Eds.), Advances in neural information processing systems 11. MA: MIT Press (1999).
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    • Detecting false financial statements using published data: Some evidence from Greece
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.