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Reseach Article

Data Mining for Detecting Carelessness or Mala Fide Intention

by Rajesh Kumar
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 74 - Number 1
Year of Publication: 2013
Authors: Rajesh Kumar
10.5120/12847-9142

Rajesh Kumar . Data Mining for Detecting Carelessness or Mala Fide Intention. International Journal of Computer Applications. 74, 1 ( July 2013), 8-11. DOI=10.5120/12847-9142

@article{ 10.5120/12847-9142,
author = { Rajesh Kumar },
title = { Data Mining for Detecting Carelessness or Mala Fide Intention },
journal = { International Journal of Computer Applications },
issue_date = { July 2013 },
volume = { 74 },
number = { 1 },
month = { July },
year = { 2013 },
issn = { 0975-8887 },
pages = { 8-11 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume74/number1/12847-9142/ },
doi = { 10.5120/12847-9142 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:41:01.651092+05:30
%A Rajesh Kumar
%T Data Mining for Detecting Carelessness or Mala Fide Intention
%J International Journal of Computer Applications
%@ 0975-8887
%V 74
%N 1
%P 8-11
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Fraud is one of the greatest challenges for the organizations, it needs a machine to be equipped with data mining algorithms , so that it can detect a crime pattern before it takes place. This paper will explore the data mining and Knowledge discovery in data base and later one of the most effective data mining techniques called Benford's law for detecting the fake entries in medical insurance claims, electricity bills, water bills etc will be discussed. Applications of Benford's law with limitations will be discussed so that machines exhibits some intelligence in its domain and later proposed to embed the Benford law in software to identify all the entries made by carelessness or with a mala fide intention .

References
  1. Stephen Battersby "Rigging of electoral polls in Iranian elections. Statistics hint at fraud in Iranian election", New scientist june24,2009.
  2. Usama Fayyad, Gregory Piatetsky-Shapiro, and Padhraic Smyth ,"To Knowledge Discovery in Databases", 6, American Association for Artificial Intelligence. AI Magazine Volume 17 Number 3 (1996)
  3. Giles," Benford's law and naturally occurring prices in certain e bay auctions". Econometrics Working Paper EWP0505, University of Victoria, Department of Economics. Forthcoming in Applied Economics Letters. ,2006.
  4. Durtschi, Cindy and William Hillison and Carl Pachini. "The Effective Use of Benford's Law to Assist in Detecting Fraud in Accounting Data", Journal of Forensic Accounting 1524-5586/Vol. V(2004): 17-34.
  5. Nigrini, M. J. (1997). Digital Analysis Tests and Statistics. Allen, Texas: The Nigrini Institute, Inc. Mark_Nigrini@classic. msn. com,1997
  6. Mark, j . Nigrini and Linda ,"The use of benford law as an aid in analytical procedure ",Auditing a journal of practice and theory ,vol16,no2,fall1997
  7. Dongdong Fu*a, Yun Q. Shi*a, Wei Sub ,"A generalized Benford's law for JPEG co efficient and its applications in image forensics"
  8. Agrawal, R. , and Psaila, G. Active Data Mining. In Proceedings of the First International Conference on Knowledge Discovery and Data Mining (KDD-95), 3–8. Menlo Park, Calif. : American Association for Artificial Intelligence,1995.
  9. Agrawal, R. ; Mannila, H. ; Srikant, R. ; Toivonen, H. ;and Verkamo, I. Fast Discovery of Association Rules. In Advances in Knowledge Discovery and Data Mining, eds,1996.
  10. Smyth, and R. Uthurusamy,. " Detection of Abrupt Changes: Theory and Application,. Englewood Cliffs, N. J. : Prentice Hall, 514–560. Menlo Park, Calif. : AAAI Press. Basseville , M. , and Nikiforov, I. V. 1993.
  11. Brachman, R. , and Anand, T. . "The Process of Knowledge Discovery in Databases: A Human-Centered Approach". In Advances in Knowledge Discovery and Data Mining, 37–58, Edition, 1996.
  12. Breiman, L. ; Friedman, J. H. ; Olshen, R. A. ; and Stone, C. J. Classification and Regression Trees,1984.
  13. Hall, J. ; Mani, G. ; and Barr, D. "Applying Computational Intelligence to the Investment Process" ,In Proceedings of CIFER-96: Computational Intelligence in Financial Engineering. Washington ,D. C. : IEEE Computer Society,1996.
  14. Langley, P. , and Simon, H. A. " Applications of Machine Learning and Rule Induction",. Communications of the ACM 38:55–64,1995.
  15. Djoko, S. ; Cook, D. ; and Holder, L. " Analyzing the Benefits of Domain Knowledge in Substructure Discovery" In Proceedings of KDD-95: First International Conference on Knowledge Discovery and Data Mining, 75–80. Menlo Park, Calif. : American Association for Artificial Intelligence,1995.
  16. Dzeroski, S. . Inductive Logic Programming for Knowledge Discovery in Databases. In Advances in Knowledge Discovery and Data Mining, eds,1996
  17. Etzioni, O. 1996. The World Wide Web: Quagmire or Gold Mine? Communications of the ACM (Special Issue on Data Mining). November 1996.
Index Terms

Computer Science
Information Sciences

Keywords

Benford law Data mining KDD Preprocessing