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Case-Based Reasoning Using Dominance-Based Decision Rules

  • Marcin Szeląg
  • Salvatore Greco
  • Jerzy Błaszczyński
  • Roman Słowiński
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6954)

Abstract

Case-based Reasoning (CBR) is a process of inferring conclusions related to a new situation by the analysis of similar cases known from the past experience. We propose to adopt in this process the Dominance-based Rough Set Approach (DRSA), that is able to handle monotonicity relationships of the type “the more similar is object y to object x with respect to the considered features, the closer is y to x in terms of the membership to a given fuzzy set X”. At the level of marginal similarity concerning single features, we consider this similarity in ordinal terms only. The marginal similarities are aggregated within decision rules underlying the general monotonicity property of comprehensive closeness of objects with respect to their marginal similarities.

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References

  1. 1.
    Błaszczyński, J., Greco, S., Słowiński, R.: Multi-criteria classification – a new scheme for application of dominance-based decision rules. European Journal of Operational Research 181(3), 1030–1044 (2007)CrossRefzbMATHGoogle Scholar
  2. 2.
    Błaszczyński, J., Greco, S., Słowiński, R., Szeląg, M.: Monotonic variable consistency rough set approaches. Int. J. of Approx. Reasoning 50(7), 979–999 (2009)MathSciNetCrossRefzbMATHGoogle Scholar
  3. 3.
    Błaszczyński, J., Słowiński, R., Szeląg, M.: Sequential covering rule induction algorithm for variable consistency rough set approaches. Information Sciences 181, 987–1002 (2011)MathSciNetCrossRefGoogle Scholar
  4. 4.
    Dubois, D., Prade, H., Esteva, F., Garcia, P., Godo, L., Lopez de Mantara, R.: Fuzzy set modelling in case-based reasoning. International Journal of Intelligent Systems 13, 345–373 (1998)CrossRefGoogle Scholar
  5. 5.
    Gilboa, I., Schmeidler, D.: A Theory of Case-Based Decisions. Number 9780521003117 in Cambridge Books. Cambridge University Press, Cambridge (2001)Google Scholar
  6. 6.
    Greco, S., Matarazzo, B., Słowiński, R.: The use of rough sets and fuzzy sets in MCDM. In: Gal, T., et al. (eds.) Multicriteria Decision Making: Advances in MCDM Models, Algorithms, Theory, and Applications, ch. 14, pp. 14.1–14.59. Kluwer Academic Publishers, Dordrecht (1999)Google Scholar
  7. 7.
    Greco, S., Matarazzo, B., Słowiński, R.: Rough sets theory for multicriteria decision analysis. European Journal of Operational Research 129(1), 1–47 (2001)MathSciNetCrossRefzbMATHGoogle Scholar
  8. 8.
    Greco, S., Matarazzo, B., Słowiński, R.: Decision rule approach. In: Figueira, J., et al. (eds.) Multiple Criteria Decision Analysis: State of the Art Surveys, ch. 13, pp. 507–562. Springer, New York (2005)Google Scholar
  9. 9.
    Greco, S., Matarazzo, B., Słowiński, R.: Dominance-based rough set approach to case-based reasoning. In: Torra, V., Narukawa, Y., Valls, A., Domingo-Ferrer, J. (eds.) MDAI 2006. LNCS (LNAI), vol. 3885, pp. 7–18. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  10. 10.
    Greco, S., Matarazzo, B., Słowiński, R.: Case-based reasoning using gradual rules induced from dominance-based rough approximations. In: Wang, G., Li, T., Grzymala-Busse, J.W., Miao, D., Skowron, A., Yao, Y. (eds.) RSKT 2008. LNCS (LNAI), vol. 5009, pp. 268–275. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  11. 11.
    Greco, S., Matarazzo, B., Słowiński, R.: Granular computing for reasoning about ordered data: the dominance-based rough set approach. In: Pedrycz, W., et al. (eds.) Handbook of Granular Computing, ch. 15, pp. 347–373. Wiley, Chichester (2008)Google Scholar
  12. 12.
    Greco, S., Pawlak, Z., Słowiński, R.: Can bayesian confirmation measures be useful for rough set decision rules? Engineering Applications of Artificial Intelligence 17(4), 345–361 (2004)CrossRefGoogle Scholar
  13. 13.
    Greco, S., Matarazzo, B., Słowiński, R., Stefanowski, J.: Variable consistency model of dominance-based rough sets approach. In: Ziarko, W., Yao, Y. (eds.) RSCTC 2000. LNCS (LNAI), vol. 2005, pp. 170–181. Springer, Heidelberg (2001)CrossRefGoogle Scholar
  14. 14.
    Hume, D.: An Enquiry Concerning Human Understanding. Clarendon Press, Oxford (1748)Google Scholar
  15. 15.
    Kolodner, J.: Case-Based Reasoning. Morgan Kaufmann, San Mateo (1993)CrossRefzbMATHGoogle Scholar
  16. 16.
    Pawlak, Z.: Rough Sets. Theoretical Aspects of Reasoning about Data. Kluwer Academic Publishers, Dordrecht (1991)zbMATHGoogle Scholar
  17. 17.
    Słowiński, R., Greco, S., Matarazzo, B.: Rough set based decision support. In: Burke, E.K., et al. (eds.) Search Methodologies: Introductory Tutorials in Optimization and Decision Support Techniques, ch. 16, pp. 475–527. Springer, New York (2005)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Marcin Szeląg
    • 1
  • Salvatore Greco
    • 2
  • Jerzy Błaszczyński
    • 1
  • Roman Słowiński
    • 1
    • 3
  1. 1.Institute of Computing SciencePoznań University of TechnologyPoznańPoland
  2. 2.Faculty of EconomicsUniversity of CataniaCataniaItaly
  3. 3.Systems Research InstitutePolish Academy of SciencesWarsawPoland

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