References

 < Day Day Up > 



Accounting and Bookkeeping. (1994). Infopedia. Funk and Wagnalls Encyclopedia.

American Institute of Certified Public Accountants. (1999). AICPA Professional Standards. New York: American Institute of Certified Public Accountants.

Ballou, D. P. & Tayi, G. K. (1999). Enhancing Data Quality in Data Warehouse Environments. Communications of the ACM, 42(1), 73-78.

Bigus, J. P. (1996). Data Mining with Neural Networks: Solving Business Problems from Application Development to Decision Support. New York: McGraw-Hill.

Borok, L. S. (1997). Data mining: Sophisticated Forms of Managed Care Modeling Through Artificial Intelligence. Journal of Health Care Finance, 23(3), 20-36.

Cabena, P.,Hadjinian, P.,Stadler, R.,Verhees, J., & Zanasi, A. (1998). Discovering Data Mining: From Concept to Implementation. Upper Saddle River, NJ: Prentice Hall PTR.

Cao, F. (1998). An Integrated Overview of Key Issues in Data Mining. Unpublished dissertation, Daltech-Dalhousie University, Canada.

Decker,P. (1998). Data Mining's Hidden Dangers. Banking Strategies, 74(2), 6-14.

Deogun, J. (1998). Feature Selection and Effective Classifiers. Journal of the American Society for Information Science, 49(5), 423-434.

Edelstein, H. (1999). Technology How-To-Mining Data Warehouses-New Software Helps Discover Information Within Databases that Queries and Reports Can't Reveal. Information week, 561, 1-6.

Fayyad, U. M.,Piatetsky-Shapiro, G., & Smyth, P. (1996). From Data Mining to Knowledge Discovery: An Overview. In U. M. Fayyad, G. Piatetsky-Shapiro, P. Smyth, & R. Uthurusamy, R. (Eds.), Advances in Knowledge Discovery and Data Mining, (pp. 1-34) Cambridge, MA: MIT Press.

Frawley, W. J.,Piatetsky-Shapiro, G., & Matheus, C. J. (1991). Knowledge. In W. J. Frawley & W. J. Piatetsky-Shapiro (Eds.), Knowledge Discovery in Databases, (pp. 1-27) Cambridge, MA: MIT Press.

Glymour, C.,Madigna, D.,Pregibon, D., & Smyth, P. (1996). Statistical Themes and Lessons for Data Mining. Data Mining and Knowledge Discovery, 1(1), 11-15.

Greenwood, Y. A. U. (1997). An Assessment of Knowledge Discovery Database and Data Mining Concept Applications and Practices in Organizations: Case of South Central Pennsylvania Firms. Master's Paper for Master of Science in Information Systems. The Pennsylvania State University at Harrisburg, Capital College.

Groveman, H. (1995). How Auditors can Detect Financial Statement Misstatement. Journal of Accountability, 83-86.

Hovy, E. (1999, April 8). Managing the Flood: Clustering, Summarizing, Translating, Reformatting, and Displaying Documents. Retrieved from the Web [Online]. Available: http://www.isi.edu/nsf/papers/hovy.htm/

Inmon, W. H. (1997). The Data Warehouse and Data Mining. Communications of the ACM, 39(11), 49-50.

Judson, D. H. (1999, April 8). Assessing the Quality of Data in Data Warehousing and Administrative Records: A Research and Statistical Approach to Data Quality [Online]. Available: http://www.isi.edu/nsf/papers/judson.htm/

Kempster, M. (1998). Digging for Data. Inform, 12(6), 22-30.

Lingras, P. J. (1998). Data Mining Using Extensions of the Rough Set Model. Journal of the American Society for Information Science, 49(5), 415-422.

Lord, A. (1997). The Impact of the New Fraud Standard on Changes in the Audit Practices of Local CPA Firms. Pennsylvania CPA Journal, 33-36.

Markovitch, J. (1995). Automated Understanding of Financial Statements Using Neural Networks and Semantic Grammars. Third Internal Conference on Artificial Intelligence Applications on Wall Street, 218-222.

McLeod, R. Jr. (1995). Management Information Systems, A Study of Computer Based Information Systems. NJ: Prentice Hall.

Musick, R.,Fidelis, K., & Slezak, T. (1999, April 8). Large-Scale Data Mining; Pilot Project in Human Genome [Online]. Available: http://www.isi.edu/nsf/papers/musick.htm/

Nazem, S. M. & Shin, B. (1999). Data Mining: New Arsenal for Strategic Decision Making. Journal of Database Management, 10(1), 39-42.

O'Callaghan, S. (1994). An Artificial Intelligence Application of Back-Propagation Neural Networks to Simulate Accountants' Assessments of Internal Control Systems Using COSO Guidelines. Dissertation, University of Cincinnati, Ohio.

O'Callaghan, S.,Walker, J., & Sale, J. (1998). Over and Under Reliance on Internal Controls: Neural Networks Versus External Auditors. Artificial Intelligence In Accounting and Auditing, 4, 55-64.

O'Leary, D. (1995). Some Privacy Issues in Knowledge Discovery: OECD Personal Privacy Guidelines. IEEE Expert, 18(8), 49-55.

Pass, S. (1997a). Data Mining: The Power of Integration. In H. F. Arner & C. Spenser (Eds.), Proceedings of the First International Conference on the Practical Application of Knowledge Discovery and Data Mining, (pp. 25-39) London: The Practical Application Company Ltd.

Pass, S. (1997b). Discovering Value in a Mountain of Data. OR/MS Today, 24-28.

Peacock, P. R. (1998). Data Mining in Marketing: Part 1. Marketing Management, 6(4), 8-18.

Peacock, P. R. (1998). Data Mining in Marketing: Part 2. Marketing Management, 7(1), 14-25.

Pendharkar, P. & Subramanian, G. (1997). Mining Software Effort Estimation Functions Using Certain Neural Networks. Working paper.

Pendharkar, P.,Rodger, J. A.,Yaverbaum, G. J.,Herman, N., & Benner, M. (1998). Association, Statistical, Mathematical and Neural Approaches for Mining Breast Cancer Patterns: A Comparative Study. Working paper.

Ruby, L. K. (1997). Solving Data Mining Problems Through Pattern Recognition. Upper Saddle River, NJ: Prentice Hall PTR.

Silberschatz, A.,Stonebraker, M., & Ullman, J. (1991). Database Systems: Achievements and Opportunities. Communications of the ACM, 34, 110-121.

Simoudis, E.,Livezey, B., & Kerber, R. (1996). Integrating Inductible and Deductive Reasoning for Data Mining. In U. M. Fayyad, G. Piatetsky-Shapiro, P. Smyth, & R. Uthurusamy (Eds.), Advances in Knowledge Discovery and Data Mining, (pp. 353-374). MA: AAAI Press/The MIT Press.

Stolfo, S. J. (1999, April 8). Data Mining Over Distributed Databases and its Application to Fraud and Intrusion Detection in Financial Information Systems [Online]. Available: http://www.cs.columbia.edu/~sal/JAM/PROJECT/nsfwhitepaper.html

Trainer, T. & Krasnewich, D. (1996). Computers. New York: McGraw-Hill.

Turpen, P. & Messina, F. (1997). Fraud Prevention and the Management Accountant. Management Accounting, 34-36.



 < Day Day Up > 



Managing Data Mining Technologies in Organizations(c) Techniques and Applications
Managing Data Mining Technologies in Organizations: Techniques and Applications
ISBN: 1591400570
EAN: 2147483647
Year: 2003
Pages: 174

flylib.com © 2008-2017.
If you may any questions please contact us: flylib@qtcs.net