Using data mining technique to enhance tax evasion detection performance

Expert Systems with Applications

Volumn 39, Issue 10, 2012, Pages 8769-8777

  Wu, Roung Shiunn ^a   Ou, C S ^a   Lin, Hui Ying ^a   Chang, She I ^a   Yen, David C ^b  

^a NATIONAL CHUNG CHENG UNIVERSITY   (Taiwan)

^b MIAMI UNIVERSITY   (United States)

Author keywords

Association rule; Data mining; Tax evasion; Value added tax

Indexed keywords

DATA MINING TECHNIQUES; DETECTION PERFORMANCE; TAX AUTHORITIES; TAX EVASION; TAX REVENUE; VALUE-ADDED TAX;

ASSOCIATION RULES; DATA MINING; DIAGNOSIS; MANAGEMENT;

TAXATION;

EID: 84862778493     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2012.01.204     Document Type: Article

References (32)

1. Agrawal, R.; Imielinski, T.; Swami, A. (1993). Mining association rules between sets of items in large databases. In: Proceedings of the ACM SIGMOD conference on management of data (pp. 207-216). Washington, DC, USA.
2. M.J.A. Berry, and G. Linoff Data mining technique: For marketing sale, and customer support 1997 John Wiley & Sons Hoboken, NJ
3. A. Datta, and H. Thomas The cube data model: A conceptual model and algebra for on-line analytical processing in data warehouses Decision Support Systems 27 1999 289 301
4. S.A. Fadairo, R. Williams, R. Trotman, and A. Onyekelu-Eze Using data mining to ensure payment integrity Journal of Government Financial Management 57 2008 22 24
5. U.M. Fayyad Data mining and knowledge discovery: Making sense out of data IEEE Expert 11 1996 20 25
6. Fayyad, U. M.; Piatesky-Shapiro, G.; Padhraic, S. (1996). From data mining to knowledge discovery: An overview. In Advance in knowledge discovery and data mining (pp. 1-34). American Association for Artificial Intelligence, Menlo Park, CA, USA.
7. W.J. Frawley, G. Paitetsjy-Shapiro, and C.J. Matheus Knowledge discovery in databases: An overview AI Magazine 13 1992 57 70
8. A. Gebauer, C.W. Nam, and R. Parsche Can reform models of value added taxation stop the VAT evasion and revenue shortfalls in the EU? Journal of Economic Policy Reform 10 2007 1 13
9. F.H. Grupe, and M.M. Owrang Data base mining discovering new knowledge and cooperative advantage Information Systems Management 12 1995 26 31
10. R. Gupta Tax evasion and financial repression Journal of Economics and Business 60 2008 517 535
11. J. Han, and Y. Fu Mining multiple-level association rules in large databases IEEE Transactions of Knowledge and Data Engineering 11 1999 798
12. J. Han, J. Pei, Y. Yin, and R. Mao Mining frequent patterns without candidate generation: A frequent-pattern tree approach Data Mining and Knowledge Discovery 8 2004 53 87
13. D. Hand Data mining: Statistics and more? The American Statistician 52 1998 112 118
14. D. Hand Statistics and data mining: Intersecting disciplines ACM SIGKDD Explorations 1 1999 16 19
15. J.N. Hoover States use BI, data warehousing to recoup unpaid taxes Intelligent Enterprise 2009 12
16. M. Huang, and S. Lin Tax evasion and audit selection International Journal of Accounting Studies 48 2009 35 66
17. W.J. Hunter, and M.A. Nelson An IRS production function National Tax Journal 49 1996 105 115
18. W.H. Inmon Building the data warehouse 1996 John Wiley & Sons, Hoboken New York
19. Jagadish, H.; Koudas, N.; Muthukrishnan, S.; Poosala, V.; Sevcik, K.; Suel, T. (1998). Optimal histograms with quality guarantees. In Proceedings of the 24th VLDB conference, New York.
20. M. Keen, and B. Lockwood The value added tax: Its causes and consequences Journal of Development Economics 92 2010 138 151
21. R.J. Kuo, S.Y. Lin, and C.W. Shih Mining association rules through integration of clustering analysis and ant colony system for health insurance database in Taiwan Expert System with Application 33 2007 794 808
22. Lent, B.; Swami, A.; Widom, J. (1997). Clustering association rules. Technical Report. Stanford InfoLab. Thirteenth International Conference on Data Engineering, April 7-11, Birmingham, UK.
23. S.H. Liao Knowledge management technologies and applications- literature review from 1995 to 2002 Expert System with Application 25 2003 155 164
24. Micci-Barrera, D.; Ramachandran, S. (2004). Improving tax administration with data mining. Available at: www.spss.com.
25. Ministry of Finance. (2011). Monthly statistics of finance. Available at: http://www.mof.gov.tw/engweb/ct.asp?xItem=53723&CtNode=683&mp=2.
26. Nycz, M.; Smok, B. (2006). Data warehouse - The source of business information. In Proceedings of the 2006 information science and IT education Joint Conference (pp. 243-250). Salfork, UK.
27. Rahman, M. S. A. (2008). Utilisation of Data mining technology within the accounting information system in the public sector: a country study - Malaysia. Doctoral Dissertation.
28. R. Rastogi, and K. Shim Mining optimized association rules with categorical and numeric attributes IEEE Transaction of Knowledge and Data Engineering 14 2002 29 50
29. P. Ravisankar, V. Ravi, G. Raghava Rao, and I. Bose Detection of financial statement fraud and feature selection using data mining techniques Decision Support Systems 50 2011 491 500
30. M.L. Songini Fraud sniffers Computerworld 2004 38
31. Y.H. Wang, M.H. Tseng, and H.C. Liao Data mining for adaptive learning sequence in English language instruction Expert System with Application 36 2009 7681 7686
32. Y. Yoon Discovery knowledge in corporate databases Information System Management 16 1999 64 71