An Intelligent Human-Computer Interaction System for Decision Support
This paper proposes a novel architecture for developing decision support systems. Unlike conventional decision support systems, the proposed architecture endeavors to reveal the decision-making process such that humans' subjectivity can be incorporated into a computerized system and, at the same time, to preserve the capability of the computerized system in processing information objectively. A number of techniques used in developing the decision support system are elaborated to make the decisionmarking process transparent. These include procedures for high dimensional data visualization, pattern classification, prediction, and evolutionary computational search. An artificial data set is first employed to compare the proposed approach with other methods. A simulated handwritten data set and a real data set on liver disease diagnosis are then employed to evaluate the efficacy of the proposed approach. The results are analyzed and discussed. The potentials of the proposed architecture as a useful decision support system are demonstrated.
[1] D.J. Power, "What Is A DSS?," The On-Line Executive Journal for
Data-Intensive Decision Support, vol. 1, no. 3, 1997, pp. 223-232.
[2] R.H. Phelps, R.M. Pliske and S.A. Mutter, "Improving decision making:
a cognitive approach," in Human Productivity Enhancement-
Organizations, Personnel, and Decision Making, vol. 2, J. Zeidner, ed.,
Praeger: USA ,1987.
[3] G.H. Bower and E. Hilgard, Theories of learning, 5th ed., Englewood
Cliffs, NJ:Prentice Hall, 1981.
[4] F. Hayes-Roth and N. Jacobstein, "The state of knowledge-based
systems," Communications of the ACM, vol. 37, no. 3, 1994, pp. 27-39.
[5] S. Franklin, Artificial Minds, Cambridge, MA: MIT Press, 1997.
[6] H. Yan, J. Zheng, Y. Jiang, C. Peng and Q. Li, "Development of a
decision support system for heart disease diagnosis using multilayer
perceptron," Proc. of the Int. Symposium on Circuits and Systems,
ISCAS '03, vol. 5, pp. 709-712, May 2003.
[7] C.E. Vasios, G.K. Matsopoulos, K.S. Nikita, N. Uzunoglu and C.
Papageorgiou, "A decision support system for the classification of eventrelated
potentials," 6th Seminar on Neural Network Applications in
Electrical Engineering, NEUREL '02, 2002, pp. 159-164.
[8] G. Bowker and S.L. Star, "Situations vs. standards in long-term, widescale
decision-making: the case of the international classification of
diseases" Intl. conference on System Sciences, vol. 4, 1991, pp. 8-11.
[9] G.D. Tattersall, K. Chichlowski and R. Limb, "Pre-processing and
visualization of decision support data for enhanced machine
classification" 1st Intl. Conf. on Intelligent Systems Engineering, pp. 275-
280, 19-21 Aug 1992.
[10] H.A. Simon, The new science of management decision, NY:Harper and
Row, 1960.
[11] G. Moorhead and R. W. Griffin, Organizational Behavior-Managing
People and Organizations, 4th ed., Houghton Mifflin:USA, 1995.
[12] W. Siedlecki, K. Siedlecka and J. Sklansky, "An overview of mapping
techniques for exploratory pattern analysis," Pattern Recognition, vol.
21, no. 5, 1988, pp. 411-429.
[13] A.K. Jain and J. Mao, "Artificial neural network for nonlinear projection
of multivariate data," in Proc. IEEE Int. Joint Conf. Neural Networks,
vol. 3, 1992, pp. 335-340.
[14] J. Mao and A.K. Jain, "Discriminant analysis neural networks," in Proc
IEEE Int. Conf. Neural Networks, vol. 1, 1993, pp. 300-305.
[15] A. König, "A survey of methods for multivariate data projection,
visualization and interactive analysis," in Proc. of the 5th Int. Conf. on
Soft Computing and Information/Intelligent Systems, IIZUKA'98, 55-59,
October 16-20, 1998.
[16] A. König and T. Michel, "DIPOL-SOM - a distance preserving
enhancement of the self-organizing map for dimensionality reduction
and multivariate data visualization," Workshop on Self-Organizing Maps
- Intelligent Systems and innovational Computing (WSOM´-03);
Sept. 11-14, 2003.
[17] J. Mao and A. K. Jain, "Artificial neural networks for feature extraction
and multivariate data projection," IEEE Trans. On Neural Networks, vol.
6, no. 2, 1995, pp. 296-317.
[18] M.M. Van Hulle, "Kernel-based equiprobabilistic topographic map
formation," Neural Computation, vol. 10, no. 7, 1998, pp.1847-1871.
[19] M.M. Van Hulle, "Faithful representations with topographic maps,"
Neural Networks, vol. 12, 1999, pp. 803-823.
[20] D.F. Specht, "Probabilistic neural networks", Neural Networks, vol.3,
1990, pp.109-118.
[21] E. Parzen, "On estimation of a probability density function and mode,"
Annals of Mathematical Statistics, vol. 33, 1962, pp. 1065-1076.
[22] J. Chen, H. Li, S. Tang and J. Sun, "A SOM-based probabilistic neural
network for classification of ship noises," IEEE Int. Conf. On
Communication, Circuits and Systems and West Sino Expositions, vol. 2,
2002, pp. 1209-1212.
[23] F. Ma, W. Wang, W. W. Tsang, Z. Tang, S. Xia and X. Tong,
"Probabilistic segmentation of volume data for visualization using SOMPNN
classifier," IEEE Symposium on Volume Visualization, vol. 169,
1998, pp. 71-78.
[24] C.M. Bishop, M. Svensén and C.K.I. Williams, "GTM: A principled
alternative to the self-organizing map," Proc. ICANN-96, 1996, pp. 165-
170.
[25] M. Herbin, N. Bonnet and P. Vautrot, "A clustering method based on the
estimation of the probability density function and on the skeleton by
influence zones: Application to image processing," Pattern Recognition
Letters, vol. 17, 1996, pp. 1141-1150.
[26] J. Vesanto (2000, April), "Neural network tool for data mining: SOM
toolbox," SOM Toolbox Team, Neural Network Research Centre,
Helsinki University of Technology, Finland.
(Online). Available: http://www.cis.hut.fi/projects/somtoolbox
[27] T. Kohonen, "Self-organized formation of topologically correct feature
maps," Biological Cybernetics, vol. 43, 1982, pp. 59-69.
[28] S. Goonatilake and S. Khebbal, Intelligent hybrid systems, John Wiley &
Sons, England, 1995.
[29] R. Nisbett and L. Ross, Human inference: strategies and shortcomings
of social judgment, Englewood Cliffs, Prentice-Hall:NJ, 1980.
[30] D. Kahneman and A. Tversky, "Subjective probability: a judgment of
representative," Cognitive Psychology, vol. 3, 1972, pp. 430-454.
[31] J. Holland, Adaptation in Natural and Artificial Systems, University of
Michigan Press, Ann Arbor, MI,1975; MIT Press, Cambridge, MA,
1992.
[32] H. Takagi, "Introduction to fuzzy systems, neural networks and genetic
algorithms," in Intelligent Systems: Fuzzy Logic, Neural Networks and
Genetic Algorithms, D. Ruan (ed.), Kluwer Academic Publishers:USA,
1997, pp 1-33.
[33] H. Takagi, Interactive evolutionary computation: system optimization
based on human subjective evaluation," IEEE Int. Conf. on Intelligent
Engineering Systems (INES-98), Vienna, Austria, pp. 1-6 Sept, 1998.
[34] H. Takagi, Visualized IEC: Interactive evolutionary computation with
multidimensional data visualization" IECON Proceedings (Industrial
Electronics Conference), vol. 4, 2000, pp. 2738-2743.
[35] R.M. Corbin, "Decisions that might not get made," in Cognitive Process
In Choice and Decision Behavior, T.S. Wallstem (ed.), Hillsdale, NJ,
Erlbaum Associates, 1980.
[36] F. Alimoglu, Combining multiple classifiers for pen-based handwritten
digit recognition, M.Sc Thesis, Institute of Graduate Studies in Science
and Engineering, Bogazici University, 1996
[37] F. Meier (2002, June), "Liver function tests," (Online). Available:
http://kidshealth.org/parent/
[38] O.L. Wong, The distribution of c-reactive protein and alpha-fetoprotein
in liver disease, (Unpublished Master Dissertation), Faculty of Medicine,
Universiti Kebangsaan Malaysia, 1996.
[39] J.O. Flores (2004, June), "Liver function tests," Gale Encyclopedia of
Medicine, (Online). Available: http://www.findarticles.com/p/articles/
[40] S.S. Cross, R.F. Harrison and R.L. Kennedy, "Introduction to neural
networks," The Lancet, vol. 346, 1995, pp. 1075-1079.
[1] D.J. Power, "What Is A DSS?," The On-Line Executive Journal for
Data-Intensive Decision Support, vol. 1, no. 3, 1997, pp. 223-232.
[2] R.H. Phelps, R.M. Pliske and S.A. Mutter, "Improving decision making:
a cognitive approach," in Human Productivity Enhancement-
Organizations, Personnel, and Decision Making, vol. 2, J. Zeidner, ed.,
Praeger: USA ,1987.
[3] G.H. Bower and E. Hilgard, Theories of learning, 5th ed., Englewood
Cliffs, NJ:Prentice Hall, 1981.
[4] F. Hayes-Roth and N. Jacobstein, "The state of knowledge-based
systems," Communications of the ACM, vol. 37, no. 3, 1994, pp. 27-39.
[5] S. Franklin, Artificial Minds, Cambridge, MA: MIT Press, 1997.
[6] H. Yan, J. Zheng, Y. Jiang, C. Peng and Q. Li, "Development of a
decision support system for heart disease diagnosis using multilayer
perceptron," Proc. of the Int. Symposium on Circuits and Systems,
ISCAS '03, vol. 5, pp. 709-712, May 2003.
[7] C.E. Vasios, G.K. Matsopoulos, K.S. Nikita, N. Uzunoglu and C.
Papageorgiou, "A decision support system for the classification of eventrelated
potentials," 6th Seminar on Neural Network Applications in
Electrical Engineering, NEUREL '02, 2002, pp. 159-164.
[8] G. Bowker and S.L. Star, "Situations vs. standards in long-term, widescale
decision-making: the case of the international classification of
diseases" Intl. conference on System Sciences, vol. 4, 1991, pp. 8-11.
[9] G.D. Tattersall, K. Chichlowski and R. Limb, "Pre-processing and
visualization of decision support data for enhanced machine
classification" 1st Intl. Conf. on Intelligent Systems Engineering, pp. 275-
280, 19-21 Aug 1992.
[10] H.A. Simon, The new science of management decision, NY:Harper and
Row, 1960.
[11] G. Moorhead and R. W. Griffin, Organizational Behavior-Managing
People and Organizations, 4th ed., Houghton Mifflin:USA, 1995.
[12] W. Siedlecki, K. Siedlecka and J. Sklansky, "An overview of mapping
techniques for exploratory pattern analysis," Pattern Recognition, vol.
21, no. 5, 1988, pp. 411-429.
[13] A.K. Jain and J. Mao, "Artificial neural network for nonlinear projection
of multivariate data," in Proc. IEEE Int. Joint Conf. Neural Networks,
vol. 3, 1992, pp. 335-340.
[14] J. Mao and A.K. Jain, "Discriminant analysis neural networks," in Proc
IEEE Int. Conf. Neural Networks, vol. 1, 1993, pp. 300-305.
[15] A. König, "A survey of methods for multivariate data projection,
visualization and interactive analysis," in Proc. of the 5th Int. Conf. on
Soft Computing and Information/Intelligent Systems, IIZUKA'98, 55-59,
October 16-20, 1998.
[16] A. König and T. Michel, "DIPOL-SOM - a distance preserving
enhancement of the self-organizing map for dimensionality reduction
and multivariate data visualization," Workshop on Self-Organizing Maps
- Intelligent Systems and innovational Computing (WSOM´-03);
Sept. 11-14, 2003.
[17] J. Mao and A. K. Jain, "Artificial neural networks for feature extraction
and multivariate data projection," IEEE Trans. On Neural Networks, vol.
6, no. 2, 1995, pp. 296-317.
[18] M.M. Van Hulle, "Kernel-based equiprobabilistic topographic map
formation," Neural Computation, vol. 10, no. 7, 1998, pp.1847-1871.
[19] M.M. Van Hulle, "Faithful representations with topographic maps,"
Neural Networks, vol. 12, 1999, pp. 803-823.
[20] D.F. Specht, "Probabilistic neural networks", Neural Networks, vol.3,
1990, pp.109-118.
[21] E. Parzen, "On estimation of a probability density function and mode,"
Annals of Mathematical Statistics, vol. 33, 1962, pp. 1065-1076.
[22] J. Chen, H. Li, S. Tang and J. Sun, "A SOM-based probabilistic neural
network for classification of ship noises," IEEE Int. Conf. On
Communication, Circuits and Systems and West Sino Expositions, vol. 2,
2002, pp. 1209-1212.
[23] F. Ma, W. Wang, W. W. Tsang, Z. Tang, S. Xia and X. Tong,
"Probabilistic segmentation of volume data for visualization using SOMPNN
classifier," IEEE Symposium on Volume Visualization, vol. 169,
1998, pp. 71-78.
[24] C.M. Bishop, M. Svensén and C.K.I. Williams, "GTM: A principled
alternative to the self-organizing map," Proc. ICANN-96, 1996, pp. 165-
170.
[25] M. Herbin, N. Bonnet and P. Vautrot, "A clustering method based on the
estimation of the probability density function and on the skeleton by
influence zones: Application to image processing," Pattern Recognition
Letters, vol. 17, 1996, pp. 1141-1150.
[26] J. Vesanto (2000, April), "Neural network tool for data mining: SOM
toolbox," SOM Toolbox Team, Neural Network Research Centre,
Helsinki University of Technology, Finland.
(Online). Available: http://www.cis.hut.fi/projects/somtoolbox
[27] T. Kohonen, "Self-organized formation of topologically correct feature
maps," Biological Cybernetics, vol. 43, 1982, pp. 59-69.
[28] S. Goonatilake and S. Khebbal, Intelligent hybrid systems, John Wiley &
Sons, England, 1995.
[29] R. Nisbett and L. Ross, Human inference: strategies and shortcomings
of social judgment, Englewood Cliffs, Prentice-Hall:NJ, 1980.
[30] D. Kahneman and A. Tversky, "Subjective probability: a judgment of
representative," Cognitive Psychology, vol. 3, 1972, pp. 430-454.
[31] J. Holland, Adaptation in Natural and Artificial Systems, University of
Michigan Press, Ann Arbor, MI,1975; MIT Press, Cambridge, MA,
1992.
[32] H. Takagi, "Introduction to fuzzy systems, neural networks and genetic
algorithms," in Intelligent Systems: Fuzzy Logic, Neural Networks and
Genetic Algorithms, D. Ruan (ed.), Kluwer Academic Publishers:USA,
1997, pp 1-33.
[33] H. Takagi, Interactive evolutionary computation: system optimization
based on human subjective evaluation," IEEE Int. Conf. on Intelligent
Engineering Systems (INES-98), Vienna, Austria, pp. 1-6 Sept, 1998.
[34] H. Takagi, Visualized IEC: Interactive evolutionary computation with
multidimensional data visualization" IECON Proceedings (Industrial
Electronics Conference), vol. 4, 2000, pp. 2738-2743.
[35] R.M. Corbin, "Decisions that might not get made," in Cognitive Process
In Choice and Decision Behavior, T.S. Wallstem (ed.), Hillsdale, NJ,
Erlbaum Associates, 1980.
[36] F. Alimoglu, Combining multiple classifiers for pen-based handwritten
digit recognition, M.Sc Thesis, Institute of Graduate Studies in Science
and Engineering, Bogazici University, 1996
[37] F. Meier (2002, June), "Liver function tests," (Online). Available:
http://kidshealth.org/parent/
[38] O.L. Wong, The distribution of c-reactive protein and alpha-fetoprotein
in liver disease, (Unpublished Master Dissertation), Faculty of Medicine,
Universiti Kebangsaan Malaysia, 1996.
[39] J.O. Flores (2004, June), "Liver function tests," Gale Encyclopedia of
Medicine, (Online). Available: http://www.findarticles.com/p/articles/
[40] S.S. Cross, R.F. Harrison and R.L. Kennedy, "Introduction to neural
networks," The Lancet, vol. 346, 1995, pp. 1075-1079.
@article{"International Journal of Information, Control and Computer Sciences:58962", author = "Chee Siong Teh and Chee Peng Lim", title = "An Intelligent Human-Computer Interaction System for Decision Support", abstract = "This paper proposes a novel architecture for developing decision support systems. Unlike conventional decision support systems, the proposed architecture endeavors to reveal the decision-making process such that humans' subjectivity can be incorporated into a computerized system and, at the same time, to preserve the capability of the computerized system in processing information objectively. A number of techniques used in developing the decision support system are elaborated to make the decisionmarking process transparent. These include procedures for high dimensional data visualization, pattern classification, prediction, and evolutionary computational search. An artificial data set is first employed to compare the proposed approach with other methods. A simulated handwritten data set and a real data set on liver disease diagnosis are then employed to evaluate the efficacy of the proposed approach. The results are analyzed and discussed. The potentials of the proposed architecture as a useful decision support system are demonstrated.
", keywords = "Interactive evolutionary computation, multivariate data projection, pattern classification, topographic map.", volume = "1", number = "7", pages = "2113-10", }
