Risk-Management by Numerical Pattern Analysis in Data-Mining
In this paper a new method is suggested for risk
management by the numerical patterns in data-mining. These patterns
are designed using probability rules in decision trees and are cared to
be valid, novel, useful and understandable. Considering a set of
functions, the system reaches to a good pattern or better objectives.
The patterns are analyzed through the produced matrices and some
results are pointed out. By using the suggested method the direction
of the functionality route in the systems can be controlled and best
planning for special objectives be done.
[1] D. T. Larose, "Discovering Knowledge in Data: An Introduction to Data
Mining," Copyright C 2005 John Wiley & Sons, Inc. Ch 1, pp.2-4.
[2] J. Pei, Shambhu J. Upadhyaya, Faisal Farooq and Venugopal
Govindaraju, "Data Mining for Intrusion Detection: Techniques,
Applications and Systems," Proceedings of the 20th International
Conference on Data Engineering (ICDE-04) ┬® 2004 IEEE.
[3] E. Bloedorn, "Mining Aviation Safety Data: A Hybrid Approach," The
MITRE Corporation, 2000.
[4] D. Kuonen, "A Statistical Perspective of Data Mining," published by
CRM Today, December 2004, in CRM Zine (Vol. 48).
[5] V. Karasova, "Spatial data mining as a tool for improving geographical
models," Master's Thesis, Helsinki University of Technology, 2005,
pp.6-7.
[6] S. Laxman, and P S Sastry, "A survey of temporal data mining,"
Sadhana Vol. 31, Part 2, April 2006, ┬® Printed in India, p.173.
[7] C. Aflori, and Florin Leon, "Efficient distributed data mining using
intelligent agents," supported in part by the National University
Research Council under Grant AT no 66 / 2004.
[8] G. Piatetsky-Shapiro, Chabane Djeraba, and Lise Getoor, "What are the
grand challenges for data mining?" KDD-2006 Panel Report, SIGKDD
Explorations, Volume 8, Issue 2.
[9] J.L. 'Alvarez, J. Mata, and J.C. Riquelme, "Data mining for the
management of software development process," International Journal of
Software Engineering and Knowledge Engineering, (1994) World
Scientific Publishing Company, p.3.
[10] A.J. McGrail, E. Gulski, and E.R.S. Groot , "Data mining techniques to
access the condition of high voltage electrical plant," School of
Electrical Engineering, University of New South Wales, SYDNEY,
NSW 2052, AUSTRALIA, On behalf of WG 15.11 of Study
Committee 15, 2002.
[11] J. n B. Ordieres Meré, and Manuel Castej n Limas, "Data mining in
industrial processes," Actas del III Taller Nacional de Miner a de Datos
y Aprendizaje, TAMIDA2005, P.60.
[12] D. J. Hand, Heikki Mannila and Padhraic Smyth, "Principles of Data
Mining (Adaptive Computation and Machine Learning)," The MIT Press
(August 1, 2001), Ch 6: models and patterns.
[13] T. Menzies, and Ying Hu, "Data mining for very busy people,"
Published by the IEEE Computer Society, ┬® 2003 IEEE, P.19.
[14] U. Fayyad, Gregory Piatetsky-Shapiro and Padhraic Smyth, "From Data
Mining to Knowledge Discovery in Databases," Copyright ┬® 1996,
American Association for Artificial Intelligence, pp. 37-49.
[15] B. Thau Loo, Tyson Condie, Minos Garofalakis, David E. Gay, and
Joseph M. Hellerstein, "Declarative networking: language, execution
and optimization," SIGMOD 2006, Chicago, Illinois, USA, Copyright
2006 ACM.
[16] M. Nycz, and Barbara Smok, "Intelligent support for decision-making: a
conceptual model," Informing Science InSITE - "Where Parallels
Intersect", June 2003, P. 916-917.
[17] Xindong Wu1, "Data Mining: An AI Perspective," IEEE Computational
Intelligence Bulletin, December 2004, Vol.4 No.2..
[18] M. Karegar, A. Isazadeh, F. Fartash, T. Saderi, A. Habibizad Navin.
Data-mining by the probability-based patterns. Proceeding of the 30th
International Conference on Information Technology Integrity, ITI 2008
IEEE, June 2008.
[1] D. T. Larose, "Discovering Knowledge in Data: An Introduction to Data
Mining," Copyright C 2005 John Wiley & Sons, Inc. Ch 1, pp.2-4.
[2] J. Pei, Shambhu J. Upadhyaya, Faisal Farooq and Venugopal
Govindaraju, "Data Mining for Intrusion Detection: Techniques,
Applications and Systems," Proceedings of the 20th International
Conference on Data Engineering (ICDE-04) ┬® 2004 IEEE.
[3] E. Bloedorn, "Mining Aviation Safety Data: A Hybrid Approach," The
MITRE Corporation, 2000.
[4] D. Kuonen, "A Statistical Perspective of Data Mining," published by
CRM Today, December 2004, in CRM Zine (Vol. 48).
[5] V. Karasova, "Spatial data mining as a tool for improving geographical
models," Master's Thesis, Helsinki University of Technology, 2005,
pp.6-7.
[6] S. Laxman, and P S Sastry, "A survey of temporal data mining,"
Sadhana Vol. 31, Part 2, April 2006, ┬® Printed in India, p.173.
[7] C. Aflori, and Florin Leon, "Efficient distributed data mining using
intelligent agents," supported in part by the National University
Research Council under Grant AT no 66 / 2004.
[8] G. Piatetsky-Shapiro, Chabane Djeraba, and Lise Getoor, "What are the
grand challenges for data mining?" KDD-2006 Panel Report, SIGKDD
Explorations, Volume 8, Issue 2.
[9] J.L. 'Alvarez, J. Mata, and J.C. Riquelme, "Data mining for the
management of software development process," International Journal of
Software Engineering and Knowledge Engineering, (1994) World
Scientific Publishing Company, p.3.
[10] A.J. McGrail, E. Gulski, and E.R.S. Groot , "Data mining techniques to
access the condition of high voltage electrical plant," School of
Electrical Engineering, University of New South Wales, SYDNEY,
NSW 2052, AUSTRALIA, On behalf of WG 15.11 of Study
Committee 15, 2002.
[11] J. n B. Ordieres Meré, and Manuel Castej n Limas, "Data mining in
industrial processes," Actas del III Taller Nacional de Miner a de Datos
y Aprendizaje, TAMIDA2005, P.60.
[12] D. J. Hand, Heikki Mannila and Padhraic Smyth, "Principles of Data
Mining (Adaptive Computation and Machine Learning)," The MIT Press
(August 1, 2001), Ch 6: models and patterns.
[13] T. Menzies, and Ying Hu, "Data mining for very busy people,"
Published by the IEEE Computer Society, ┬® 2003 IEEE, P.19.
[14] U. Fayyad, Gregory Piatetsky-Shapiro and Padhraic Smyth, "From Data
Mining to Knowledge Discovery in Databases," Copyright ┬® 1996,
American Association for Artificial Intelligence, pp. 37-49.
[15] B. Thau Loo, Tyson Condie, Minos Garofalakis, David E. Gay, and
Joseph M. Hellerstein, "Declarative networking: language, execution
and optimization," SIGMOD 2006, Chicago, Illinois, USA, Copyright
2006 ACM.
[16] M. Nycz, and Barbara Smok, "Intelligent support for decision-making: a
conceptual model," Informing Science InSITE - "Where Parallels
Intersect", June 2003, P. 916-917.
[17] Xindong Wu1, "Data Mining: An AI Perspective," IEEE Computational
Intelligence Bulletin, December 2004, Vol.4 No.2..
[18] M. Karegar, A. Isazadeh, F. Fartash, T. Saderi, A. Habibizad Navin.
Data-mining by the probability-based patterns. Proceeding of the 30th
International Conference on Information Technology Integrity, ITI 2008
IEEE, June 2008.
@article{"International Journal of Information, Control and Computer Sciences:63420", author = "M. Kargar and R. Mirmiran and F. Fartash and T. Saderi", title = "Risk-Management by Numerical Pattern Analysis in Data-Mining", abstract = "In this paper a new method is suggested for risk
management by the numerical patterns in data-mining. These patterns
are designed using probability rules in decision trees and are cared to
be valid, novel, useful and understandable. Considering a set of
functions, the system reaches to a good pattern or better objectives.
The patterns are analyzed through the produced matrices and some
results are pointed out. By using the suggested method the direction
of the functionality route in the systems can be controlled and best
planning for special objectives be done.", keywords = "Analysis, Data-mining, Pattern, Risk Management.", volume = "2", number = "5", pages = "1746-5", }
