Inconsistent Dominance Principle Based Attribute Reduction in Ordered Information Systems
Dominance-based rough set is an important model for ordered decision system, in which knowledge reduction is one of the most important problems. The preference ordering of decision between objects is ignored in existed reduction. This paper proposed a knowledge reduction approach based on inconsistent dominance principle, with which two objects are discernable. Furthermore, the judgment theorems and the discernable matrix are investigated, from which we can obtain a new approach to knowledge reduction in ordered decision system.
KeywordsOrdered decision system Knowledge reduction Inconsistent dominance principle
This work is supported by the National Science and Technology Major Project (2014ZX07104-006) and the Hundred Talents Program of CAS (NO.Y21Z110A10).
- 1.Dembczyński, K., Greco, S., Kotłowski, W., Słowiński, R.: Quality of Rough Approximation in Multi-criteria Classification Problems. In: Greco, S., Hata, Y., Hirano, S., Inuiguchi, M., Miyamoto, S., Nguyen, H.S., Słowiński, R. (eds.) RSCTC 2006. LNCS (LNAI), vol. 4259, pp. 318–327. Springer, Heidelberg (2006) CrossRefGoogle Scholar
- 10.Xu, W.H., Zhang, W.X.: Knowledge reductions in inconsistent information systems based on dominance relations. Comput. Sci. 33(2), 182–184 (2006) (in Chinese)Google Scholar
- 11.Xu, W.H., Zhang W.X.: Matrix computation for assignment reduction in information systems based on dominance relations. Comput. Eng. 33(14), 4–7 (2007) (in Chinese)Google Scholar
- 14.Chen, J., Wang, G.Y., Hu, J.: Positive domain reduction based on dominance relation in inconsistent system. Comput. Sci. 35(3), 216–218, 227 (2008) (in Chinese)Google Scholar
- 15.Inuiguchi, M., Yoshioka, Y.: Several reducts in dominance-based rough set approach. In: Huynh, V.N., Nakamori, Y., Ono, H., Lawry, J., Kreinovich, V., Nguyen, H.T. (eds.) Interval/Probabilistic Uncertainty and Non-Classical Logics. ASC, vol. 46, pp. 163–175. Springer, Heidelberg (2008)CrossRefGoogle Scholar