CFP last date
20 December 2024
Reseach Article

Overview of Maintenance for Case based Reasoning Systems

by Abir Smiti, Zied Elouedi
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 32 - Number 2
Year of Publication: 2011
Authors: Abir Smiti, Zied Elouedi
10.5120/3881-5423

Abir Smiti, Zied Elouedi . Overview of Maintenance for Case based Reasoning Systems. International Journal of Computer Applications. 32, 2 ( October 2011), 49-56. DOI=10.5120/3881-5423

@article{ 10.5120/3881-5423,
author = { Abir Smiti, Zied Elouedi },
title = { Overview of Maintenance for Case based Reasoning Systems },
journal = { International Journal of Computer Applications },
issue_date = { October 2011 },
volume = { 32 },
number = { 2 },
month = { October },
year = { 2011 },
issn = { 0975-8887 },
pages = { 49-56 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume32/number2/3881-5423/ },
doi = { 10.5120/3881-5423 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:18:09.155631+05:30
%A Abir Smiti
%A Zied Elouedi
%T Overview of Maintenance for Case based Reasoning Systems
%J International Journal of Computer Applications
%@ 0975-8887
%V 32
%N 2
%P 49-56
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The success of a Case Based Reasoning (CBR) system depends on the quality of case data and the speed of the retrieval process that can be expensive in time especially when the number of cases gets large. To guarantee this quality, maintenance the contents of a case base becomes necessarily. As a result, the research area of Case Base Maintenance (CBM) has drawn more and more attention to CBR systems. This paper provides a snapshot of the state of the art, reviewing some important methods of maintaining case based reasoning. We introduce a framework for distinguishing these methods and compare and analyze them. In addition, this paper also presents simulations on data sets from U.C.I repository to show the effectiveness of some CBM methods taking into account the accuracy, the size and the retrieval time of case bases. Our simulation results which are obtained by compared well known reduction techniques show that these CBM methods have good storage reduction ratios, satisfying classification accuracies and short retrieval time.

References
  1. A. Aamodt and E. Plaza, Case-Based Reasoning: Foundational Issues, Methodological Variations, and System Approaches, Artificial Intelligence Communications 7, 7, 1, 39-52 (1994)
  2. D. B. Leake, Case-Based Reasoning: Experiences, Lessons and Future Directions, MIT Press, Cambridge, MA, USA (1996)
  3. Z. Sun and G. Finnie, A Unified Logical Model for CBR-based E-commerce Systems, International Journal of Intelligent Systems, 1-28 (2005)
  4. D. B. Leake and D. C. Wilson, Maintaining Case-Based Reasoners: Dimensions And Directions, Computational Intelligence, 17, 196-213 (2001).
  5. T. Reinartz , I. Iglezakis and T. Roth-Berghofer , On quality measure for case base maintenance. Advances in Case-Based Reasoning, 5th European Workshop, EWCBR 2000, 247-259, (2000).
  6. J. Zhu, Similarity Metrics and Case Base Maintenance, the School of Computing Science, University of British Columbia, Thesis (1998).
  7. B. Smyth and M. T. Keane, Remembering To Forget: A Competence-Preserving Case Deletion Policy for Case-Based Reasoning Systems, Proceeding of the 14th International Joint Conference on Artificial Intelligent, 377-382 (1995).
  8. 8. S. Minton, Quantitative Results Concerning the Utility of Explanation-based Learning, Artif. Intell., 363-391 (1990).
  9. I. Iglezakis and C. E. Anderson, Towards the use of case properties for maintaining case-based reasoning systems, Proceedings of the Pacific Rim Knowledge Acquisition Workshop (PKAW), 135-146 (2000).
  10. P. Rong, Y. Qiang and P. S. Jialin, Mining competent case bases for case-based reasoning, Artif. Intell., 171, 1039-1068 (2007).
  11. S. ck Shiu, Y. Li and X. Z.Wang, Using Fuzzy Integral to Model Case-Base Competence, Workshop on Soft Computing in Case-Based Reasoning, 59-64 (2001).
  12. B. Smyth and E. McKenna, Modeling the Competence of Case-Bases, EWCBR, 208-220 (1998).
  13. R. Pan, Q. Yang and S. J. Pan, Mining competent case bases for case-based reasoning, Artif. Intell., 171, 1039-1068 (2007).
  14. S. C. K. Shiu, D. S. Yeung, C. H. Sun and X. Wang, Maintaining Case-Based Reasoning Systems Using Fuzzy Decision Trees, EWCBR, 285-296 (2000).
  15. G. Cao, Simon C. K. Shiu and Xizhao Wang, A Fuzzy-Rough Approach for Case Base Maintenance, ICCBR, 118-130 (2001).
  16. S. C. K. Shiu, D. S. Yeung, C. H. Sun and X. Wang, Transferring Case Knowledge to Adaptation Knowledge: An Approach for Case-Base Maintenance, Computational Intelligence, 17, 295-314 (2001).
  17. Q. Yang and J. Wu, Keep It Simple: A Case-Base Maintenance Policy Based on Clustering and Information Theory, Canadian Conference on AI, 102-114 (2000).
  18. S. Markovitch and P. D. Scott, The Role of Forgetting in Learning, In Proceedings of the Fifth International Conference on Machine Learning, 459-465 (1988).
  19. S. Minton, Qualitative Results Concerning the Utility of Explanation-Based Learning, Artificial Intelligence, 42, 363-391 (1990).
  20. M. K. Haouchine, B. Chebel-Morello and N. Zerhouni, Competence-Preserving Case-Deletion Strategy for Case-Base Maintenance, Similarity and Knowledge Discovery in Case-Based Reasoning Workshop. 9th European Conference on Case-Based Reasoning ECCBR'08, 171-184 (2008).
  21. C. H. Chou, B. H Kuo and F. Chang, The Generalized Condensed Nearest Neighbor ule as A Data Reduction Method, Pattern Recognition, International Conference on, IEEE Computer Society, 2, 556-559 (2006).
  22. G. Ritter and H. Woodruff and S. Lowry and T.Isenhour, An algorithm for a selective nearest neighbor decision rule, IEEE Transactions on Information Theory, 21, 665-669 (1975).
  23. W. Gates, The Reduced Nearest Neighbor Rule, IEEE Transactions on Information Theory, 18, 3, 431-433 (1972).
  24. A. Smiti and Z. Elouedi, COID : Maintaining case method based on Clustering, Outliers and Internal Detection, book chapter in Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing 2010, SNPD'10, Springer Berlin / Heidelberg, 295, 39-52 (2010).
  25. A. Smiti and Z. Elouedi, WCOID: Maintaining Case-Based Reasoning systems using Weighting, Clustering, Outliers and Internal cases Detection, International Conference on Intelligent Systems Design and Applications (ISDA), IEEE Computer Society (2011).
  26. D. W. Aha, and D.Kibler, and M. K. Albert, Instance-based learning algorithms, Machine Learning, Springer Netherlands, 6, 37-66 (1991).
  27. M. Salamo and E. Golobardes, Hybrid Deletion Policies for Case Base Maintenance, Proceedings of FLAIRS-2003, AAAI Press, 150-154 (2003).
  28. M. Salamo and E. Golobardes, Dynamic Case Base Maintenance for a Case-Based Reasoning System, IBERAMIA, 93-103 (2004).
  29. A. Asuncion and D.J. Newman, UCI Machine Learning Repository. University of California, Irvine, School of Information and Computer Sciences, http://www.ics.uci.edu/mlearn (2007).
  30. B. Smyth, Case-Base Maintenance, Proceedings of the 11th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems IEA/AIE, London, UK, 507-516 (1998).
  31. D. L. Wilson, Asymptotic Properties of Nearest Neighbor Rules Using Edited Data, IEEE Transactions on Systems Man and Cybernetics, 2, 408-421 (1972).
  32. D. Guan, W. Yuan, Lee, Y. K. Lee, S. Lee, Nearest neighbor editing aided by unlabeled data, Inf. Sci., 179, 13, 2273-2282 (2009).
  33. Q. Yang and J. Zhu, A case addition policy for case-base maintenance. Computational Intelligence Journal, A Special Issue on Case-Base Maintenance. Blackwell Publishers, Boston MA UK, 17(2): 250-262 (2001).
Index Terms

Computer Science
Information Sciences

Keywords

Case based reasoning Case base maintenance evaluating case base Case base partitioning Clustering Selection method Case base optimization