Dominance-based rough set approach and knowledge reductions in incomplete ordered information system
Information Sciences: an International Journal
Attribute reduction based on evidence theory in incomplete decision systems
Information Sciences: an International Journal
Interval ordered information systems
Computers & Mathematics with Applications
Credible rules in incomplete decision system based on descriptors
Knowledge-Based Systems
Knowledge reduction and matrix computation in inconsistent ordered information systems
International Journal of Business Intelligence and Data Mining
Set-valued ordered information systems
Information Sciences: an International Journal
Attribute reduction and optimal decision rules acquisition for continuous valued information systems
Information Sciences: an International Journal
A Time-Reduction Strategy to Feature Selection in Rough Set Theory
RSKT '09 Proceedings of the 4th International Conference on Rough Sets and Knowledge Technology
Dominance-based rough set approach to incomplete interval-valued information system
Data & Knowledge Engineering
Uncertainty Measures of Roughness of Knowledge and Rough Sets in Ordered Information Systems
ICIC '07 Proceedings of the 3rd International Conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence
Positive approximation: An accelerator for attribute reduction in rough set theory
Artificial Intelligence
Consistency and fuzziness in ordered decision tables
RSKT'08 Proceedings of the 3rd international conference on Rough sets and knowledge technology
Order-based decision rules acquisition in continuous-valued decision information systems
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 2
Knowledge approximation and rule acquisition based on VPRS in ordered information systems
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 4
The Knowledge Engineering Review
Generalized distribution reduction in inconsistent decision systems based on dominance relations
RSKT'10 Proceedings of the 5th international conference on Rough set and knowledge technology
Neighborhood systems-based rough sets in incomplete information system
Knowledge-Based Systems
Dominance-based fuzzy rough approach to an interval-valued decision system
Frontiers of Computer Science in China
Discernibility-matrix method based on the hybrid of equivalence and dominance relations
RSFDGrC'11 Proceedings of the 13th international conference on Rough sets, fuzzy sets, data mining and granular computing
Valued dominance-based rough set approach to incomplete information system
Transactions on computational science XIII
Distance: A more comprehensible perspective for measures in rough set theory
Knowledge-Based Systems
Knowledge reduction based on evidence reasoning theory in ordered information systems
KSEM'06 Proceedings of the First international conference on Knowledge Science, Engineering and Management
An intuitionistic fuzzy dominance---based rough set
ICIC'11 Proceedings of the 7th international conference on Intelligent Computing: bio-inspired computing and applications
Uncertainty measures of roughness based on interval ordered information systems
ICIC'11 Proceedings of the 7th international conference on Advanced Intelligent Computing
Evaluation of the decision performance of the decision rule set from an ordered decision table
Knowledge-Based Systems
Feature selection using rough entropy-based uncertainty measures in incomplete decision systems
Knowledge-Based Systems
Attribute reduction for dynamic data sets
Applied Soft Computing
A Comparative Study of Ordered and Covering Information Systems
Fundamenta Informaticae
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Rough sets theory has proved to be a useful mathematical tool for classification and prediction. However, as many real-world problems deal with ordering objects instead of classifying objects, one of the extensions of the classical rough sets approach is the dominance-based rough sets approach, which is mainly based on substitution of the indiscernibility relation by a dominance relation. In this article, we present a dominance-based rough sets approach to reasoning in incomplete ordered information systems. The approach shows how to find decision rules directly from an incomplete ordered decision table. We propose a reduction of knowledge that eliminates only that information that is not essential from the point of view of the ordering of objects or decision rules. © 2005 Wiley Periodicals, Inc. Int J Int Syst 20: 13–27, 2005.