Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 31100
Methods for Case Maintenance in Case-Based Reasoning

Authors: A. Lawanna, J. Daengdej


Case-Based Reasoning (CBR) is one of machine learning algorithms for problem solving and learning that caught a lot of attention over the last few years. In general, CBR is composed of four main phases: retrieve the most similar case or cases, reuse the case to solve the problem, revise or adapt the proposed solution, and retain the learned cases before returning them to the case base for learning purpose. Unfortunately, in many cases, this retain process causes the uncontrolled case base growth. The problem affects competence and performance of CBR systems. This paper proposes competence-based maintenance method based on deletion policy strategy for CBR. There are three main steps in this method. Step 1, formulate problems. Step 2, determine coverage and reachability set based on coverage value. Step 3, reduce case base size. The results obtained show that this proposed method performs better than the existing methods currently discussed in literature.

Keywords: Case-based Reasoning, coverage, reachability, Case Base Maintenance

Digital Object Identifier (DOI):

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1295


[1] D.W. Aha, "Feature Weighting for Lazy Learning Algorithms," Data Mining Perspective. Norwell. Mass.: Kluwer., pp.13-32., 1998.
[2] Q. Yang and J. Wu, "Keep It Simple: A Case-Base Maintenance Policy Based on Clustering and Information Theory," Proceedings of the 13th Biennial Conference of the Canadian Society on Computational Studies of Intelligence: Advances in Artificial Intelligence, 102-114, 2000.
[3] R. Thomas and B. Roth, "Knowledge Maintenance of Case-Based Reasoning SystemsÔÇöThe SIAM Methodology," volume 262 of Dissertationen zur K├╝nstlichen Intelligenz. Akademische Verlagsgesellschaft Aka GmbH / IOS Press., Berlin, Germany, 2003.
[4] S. Minton, "Qualitative Results Concerning the Utility of Explanation- Based Learning," Artificial Intelligence, vol 42, pp. 363-391, 1990.
[5] B. Smyth and M. Keane, "Remembering to forget: A Competence- Preserving Case Deletion Policy for Case-Based Reasoning Systems," In Proceedings of the 13th International Joint Conference on Artificial Intelligence., pp. 377-382, 1995.
[6] J. Zhu and Q. Yang, "Remembering to add: Competence-preserving case-addition policies for case based reasoning," 1998.
[7] S. Massie, S. Craw, and N. Wiratunga, "Complexity-guided case discovery for case based reasoning," In: The Twentieth National Conference on Artificial Intelligence, pp. 216-221, 2005.
[8] K. Haouchine, B. Chebel-Morello, and N. Zerhouni, "Competence- Preserving Case-Deletion Strategy for Case-base Maintenance.," Uncertainty, Similarity, andKnowledge Discovery in Case-Based Reasoning workshop. 9th European Conference on CBR.
[9] G. Cao, S. Shiu, and X. Wang X, "A fuzzy-rough approach for case base maintenance Cataltepe Z, Abu-mostafa YS, Magdon-ismail M (1999) No free lunch for early stopping. Neural Computation, pp. 11:995-1009, 2001.
[10] R. W. Lucky, "Automatic equalization for digital communication," Bell Syst. Tech. J., vol. 44, no. 4, pp. 547-588, Apr. 1965.
[11] M. Salam'o and E. Golobardes, "Global, local and mixed rough sets case base maintenance techniques," In: Proceedings of the 6th Catalan Conference on Artificial Intelligence, IOS Press, pp 127-134, 2004.
[12] N. Arshadi and I. Jurisica, "Maintaining Case-Based Reasoning Systems: A Machine Learning Approach," Advances in Case-Based Reasoning: Proc. Seventh European Conf., pp. 17-31, 2004.
[13] R. Pan, Q. Yang, J.J. Pan, and L. Li , "Competence Driven Case-Base Mining," AAAI .2005, pp. 228-233, 2005.
[14] S.S. Wang and Yeung., "Transferring Case Knowledge to Adaptation Knowledge: An Approach for Case-base Maintenance," Computational Intelligence., 2001.
[15] C. Yang, R. Orchard, B. Farley, and M. Zaluski M, "Authoring Cases from Free-Text Maintenance Data," Machine Learning and Data Mining in Pattern Recognition , Springer Berlin, Heidelberg., 2004.
[16] N. Zhi-wei, L. Yu, and L. Feng-gang, "Case base maintenance based on outlier data mining," Proc.4th Intl.Conf.on Machine Learning and Cybernetics., Guangzhou., pp. 2,861-2,864, 2005.
[17] J. Daengdej, "Adaptable Case Base Reasoning Techniques For Dealing With Highly Noise Cases," The University of New England, 1998.
[18] S. Bogaerts and D. Leake, "IUCBRF Lesson: Case Base Maintenance Policies," 2005.
[19] B. Smyth, "Case-base maintenance," In Proceedings of the 11th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, Springer-Verlag, 1998.