Communications of the ACM
Optimized generalized decision in dominance-based rough set approach
RSKT'07 Proceedings of the 2nd international conference on Rough sets and knowledge technology
Dominance-based rough sets using indexed blocks as granules
RSKT'08 Proceedings of the 3rd international conference on Rough sets and knowledge technology
A roadmap from rough set theory to granular computing
RSKT'06 Proceedings of the First international conference on Rough Sets and Knowledge Technology
RSFDGrC'05 Proceedings of the 10th international conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing - Volume Part I
Bit-vector representation of dominance-based approximation space
Transactions on rough sets XIII
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This paper introduces the representation of Dominance-based approximation space by binary neighborhood systems introduced by Lin. We use blocks indexed by pairs of decision values as elementary neighborhoods or granules for computing approximations of generalized multiple criteria decision tables. The concept of generalized decisions was introduced by Dembczynski et al. as a generalization of DRSA (Dominance-based Rough Set Approach) where criteria and decision attribute in a decision table may be assigned a range of values. We show that binary neighborhood systems provide a uniform representation of both singleton and generalized multicriteria decision tables. The main task is to determine the family of binary relations to capture inconsistency caused by violating the dominance principle. In addition, some interesting relationships among lower, upper approximations and boundary sets are presented. The proposed approach is demonstrated by examples.