Ongoing management and application of discovered knowledge in a large regulatory organization

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Ongoing management and application of discovered knowledge in a large regulatory organization: a case study of the use and impact of NASD Regulation's Advanced Detection System (RADS)

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International Conference on Knowledge Discovery and Data Mining archive
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining table of contents

Boston, Massachusetts, United States

Pages: 44 - 53

Year of Publication: 2000

ISBN:1-58113-233-6

Author

Ted E. Senator

NASD Regulation, Inc., 5 Choke Cherry Road, Rockville, MD

Sponsors

SIGKDD: ACM Special Interest Group on Knowledge Discovery in Data
AAAI : Am Assoc for Artifical Intelligence
SIGART: ACM Special Interest Group on Artificial Intelligence
SIGMOD: ACM Special Interest Group on Management of Data

Publisher

ACM New York, NY, USA

Bibliometrics

Downloads (6 Weeks): 7, Downloads (12 Months): 56, Citation Count: 3

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REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

	1	Tom Fawcett , Foster Provost, Activity monitoring: noticing interesting changes in behavior, Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining, p.53-62, August 15-18, 1999, San Diego, California, United States [doi>10.1145/312129.312195]
	2	Usama M. Fayyad , Gregory Piatetsky-Shapiro , Padhraic Smyth , Ramasamy Uthurusamy, Advances in knowledge discovery and data mining, American Association for Artificial Intelligence, Menlo Park, CA, 1996
	3	Goldberg, Henry G. and Senator, Ted E., Break Detection Systems in AI Approaches to Fraud Detection and Risk Management, Technical Report WS-97-07, AAAI Press, 1997.
	4	Jensen, David, Unique Challenges of Managing Inductive Knowledge, in AI and Knowledge Management. AAAI Technical Report WS-97-09, AAAI Press, 1997.
	5	Kirkland, James D., Senator, Ted E., et. al., The NASD Regulation Advanced Detection System (ADS), AI Magazine 20(1):55-67, 1999.
	6	Gregory Piatetsky-Shapiro, Data mining and knowledge discovery Internet resources, Advances in knowledge discovery and data mining, American Association for Artificial Intelligence, Menlo Park, CA, 1996
	7	Senator, Ted E. and Goldberg, Henry G., Break Detection Systems. To appear in W. Kloesgen and J. Zytkow (eds.), Handbook of Knowledge Discovery and Data Mining, 2000.

CITED BY 3

	Nilesh Dalvi , Pedro Domingos , Mausam , Sumit Sanghai , Deepak Verma, Adversarial classification, Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining, August 22-25, 2004, Seattle, WA, USA
	Abraham Bernstein , Foster Provost , Shawndra Hill, Toward Intelligent Assistance for a Data Mining Process: An Ontology-Based Approach for Cost-Sensitive Classification, IEEE Transactions on Knowledge and Data Engineering, v.17 n.4, p.503-518, April 2005
	Dongshan Xing , Mark Girolami, Employing Latent Dirichlet Allocation for fraud detection in telecommunications, Pattern Recognition Letters, v.28 n.13, p.1727-1734, October, 2007