A Mining Method to Create Knowledge Map by Analysing the Data Resource
Citation
Arti Gupta , Prof. N. T. Deotale. "A Mining Method to Create Knowledge Map by Analysing the Data Resource", International Journal of Engineering Trends and Technology (IJETT), V9(9),430-435 March 2014. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group
Abstract
The fundamental step in measuring the robustness of a system is the synthesis of the so-called Process Map. This is generally based on the user’s raw data material. Process Maps are of fundamental importance towards the understanding of the nature of a system in that they indicate which variables are causally related and which are particularly important. This paper represent the system Map or business structure map to understand business criteria studying the various aspects of the company. The business structure map or knowledge map or Process map are used to increase the growth of the company by giving some useful measures according to the business criteria. This paper also deals with the different company strategy to reduce the risk factors. Process Map is helpful for building such knowledge successfully. Making decisions from such map in a highly complex situation requires more knowledge and resources.
References
[1] B. Kosko, Fuzzy cognitive maps, International Journal of Man- Machin Studies, vol. 24, no. 3, pp.
[2] J. Aguilar, A survey about fuzzy cognitive map papers, Internationa Journal of Computational Cognition, vol. 3,no. 2, pp. 27-33, 2005.
[3 ] L. Rodriguez-Repiso, R. Setchi , and J. L. Salmeron, Modelling IT projects success with fuzzy cognitive maps,Expert Systems with Applications, vol. 32, no. 2, pp. 543-559, 2007.
[4] Z. Peng, B. Yang, C. Liu , Z. Tang, and J. Yang, Research on one fuzzy cognitive map classifier, (in Chinese), Application Research of Computers , vol. 26 , no. 5 , pp.1757-1759, 2009.
[5] T. Hong and I. Han , Knowledge-based data mining of news information on the Internet using cognitive maps and neural networks, Expert Systems with Applications, vol. 23, no. 1, pp. 1-8, 2002.
[6] E. I. Papageorgiou , Learning algorithms for Fuzzy cognitive maps?a review study , IEEE Trans on Systems, Man and Cybernetics , vol. 42, no. 2, pp. 150-163, 2012.
[7] J. A.Dickerson and B. Kosko,Virtual worlds as fuzzy cognitive maps Presence , vol. 3 , no. 2, pp. 173-189, 1994.
[8] M. Schneider, E. Shnaider , A. Kande l, and G. Chew , Constructing fuzzy cognitive maps, in Proc. 1995 IEEE International Conference on uzzy Systems , Yokohama , Japan , 1995, pp. 2281-2288.
[9] K. E. Parsopoulos, E. I. Papageorgiou , P. P. Groumpos, and M. N. Vrahatis, A first study of Fuzzy cognitive maps learning using Particle swarm optimization, in Proc. 2003 Congress on Evolutionary Computation, 2003, pp. 1440 1447.
[10] W. Stach, L. Kurgan , W. Pedrycz, and M. Reformat , Learning Fuzzy cognitive maps with required precision using genetic algorithm approach , Electronics Letters, vol.40, no. 24, pp. 1519-1520, 2004.
[11] G. Allen and J. Marczyk ,Tutorial on Complexity management for decision-making, pdf, 2012.
[12] J. Marczyk ,A New Theory of Risk And Rating, Trento:Editrice Uni Service , 2009.
[13] D. V. Stewar,The design structure matrix: A Method for managing the design of complex systems, IEEE Transactions on Engineering Management,vol. EM-28, no. 3, pp.71-74,1981.
[14] S. Aumonier , Generalized correlation power Analysis , in Proc. ECRYPT Workshop on Tools For Cryptanalysis Krakw,Poland,2007.
[15] C. E. Shannon , A mathematical theory of communication, Bell System Technical Journal, vol. 27, pp.379-423, 1948.
[16] B. Lent, A. Swami , and J. Widom , Clustering Association rules, in Proc. 13th International Conference on DataEngineering,Birmingham, England, 1997, pp. 220
Keywords
business structure, knowledge map, robustness resources, system map.