Browse > Article

Introduction to a New Reasoning Technique: Code Arrangement-Based Reasoning  

Kang, Min-Cheol (아주대학교 경영대학 e-비즈니스학부)
Im, Ho-Youn (아주대학교 일반대학원 경영정보학과)
Publication Information
Asia pacific journal of information systems / v.14, no.3, 2004 , pp. 77-92 More about this Journal
Abstract
When humans make decisions, they differentiate classifications of individual attribute variables that affect the decisions according to the importance and pattern of each attribute variables. The present study examines the practicality of the proposed Code Arrangement-Based Reasoning(CABR), which resembles the human's way of reasoning. To this end, we developed a CABR technique that classifies each attribute variable affecting significant impacts on the target variable into a cluster and assigns a code to the cluster. For verifying the proposed technique, both case-based reasoning and CABR were used for the customer continuance judgment problem of an automobile insurance company. Results indicated that the performance of CABR is close to the one of the case-based reasoning. The CABR also shows the possibility of using bio-informatics techniques for organizational data analysis in the future.
Keywords
Code Arrangement-based Reasoning; Case-based; Reasoning;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Berry, M.J.A. and Linoff, G., Mastering Data Mining, John Wiley & Sons Inc., 2000
2 Gary, B.F. and Corne, D.W., 'Computational intelligence in bioinformatics,' Biosystems, Vol. 72, Issues 1-2, November 2003, pp. 1-4   DOI   ScienceOn
3 Riesbeck, C.K. and Schank, R.L., Inside Case- Based Reasoning, Lawrence Erlbaum Associates, 1989.
4 Watson, I., Applyiηg Case-Based Reasoning: Techniques for Enterprise System, Morgan Kaufmann, 1997
5 Berry, M.J.A. and Linoff, G., Data Mining Techniques for Marketing, Sales, and Customer Support, John Wiley & Sons Inc., 1997
6 Pal, S.K., 'Soft Data Mining Computational Theory of Perceptions, and Rough Fuzzy Approach,' Information Sciences, Vol. 163, Issues 1-3, June 2004, pp. 5-12   DOI   ScienceOn
7 Zaki， M.J. and Wang, J.T.L., 'Special issue on data management in bioinformatics,' Information Systems, Vol. 28, Issue 4, June 2003, pp. 241-242   DOI   ScienceOn
8 김상운, 패턴 인식 및 학습, 흥릉과학출판사，2003
9 Doak, J., An Evaluation of Feature Selection Methods and Their Application to Computer Security, Technical Report CES-92-18, Department of Computer Science, Davis, CA., University of California, 1992
10 Nelson, M.M. and Illingworth, W.T., A Practical Guide to Neural Nets, Addison Wesley Inc., 1991
11 Gose, Johnsonbaugh R. and Jost, S., Pattern Recognition and Image Analysis, Prentice Hall, 1996
12 Duda, R.O., Hart, P.E. and Stock D.G., Pattern Classfication，2nd ed，John Wiley & Sons, 2001
13 Kim, G.H, An, S.H. and Kang, K.I., 'Comparison of Construction Cost Estimating Models Based on Regression Analysis, Neural Networks, and Case-Based Reasoning,' Building and Environment, in press, 2004
14 이성환, 패턴 인식의 원리 홍릉과학출판사, 1994