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.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
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)
Błaszczyński, J., Greco, S., Słowiński, R., Szeląg, M.: Monotonic variable consistency rough set approaches. Int. J. of Approx. Reasoning 50(7), 979–999 (2009)
Błaszczyński, J., Słowiński, R., Szeląg, M.: Sequential covering rule induction algorithm for variable consistency rough set approaches. Information Sciences 181, 987–1002 (2011)
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)
Gilboa, I., Schmeidler, D.: A Theory of Case-Based Decisions. Number 9780521003117 in Cambridge Books. Cambridge University Press, Cambridge (2001)
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)
Greco, S., Matarazzo, B., Słowiński, R.: Rough sets theory for multicriteria decision analysis. European Journal of Operational Research 129(1), 1–47 (2001)
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)
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)
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)
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)
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)
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)
Hume, D.: An Enquiry Concerning Human Understanding. Clarendon Press, Oxford (1748)
Kolodner, J.: Case-Based Reasoning. Morgan Kaufmann, San Mateo (1993)
Pawlak, Z.: Rough Sets. Theoretical Aspects of Reasoning about Data. Kluwer Academic Publishers, Dordrecht (1991)
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)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Szeląg, M., Greco, S., Błaszczyński, J., Słowiński, R. (2011). Case-Based Reasoning Using Dominance-Based Decision Rules. In: Yao, J., Ramanna, S., Wang, G., Suraj, Z. (eds) Rough Sets and Knowledge Technology. RSKT 2011. Lecture Notes in Computer Science(), vol 6954. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24425-4_53
Download citation
DOI: https://doi.org/10.1007/978-3-642-24425-4_53
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-24424-7
Online ISBN: 978-3-642-24425-4
eBook Packages: Computer ScienceComputer Science (R0)