Rough-set reasoning about uncertain data
Fundamenta Informaticae - Special issue: rough sets
Rough set approach to incomplete information systems
Information Sciences: an International Journal
Rules in incomplete information systems
Information Sciences: an International Journal
On semantic issues connected with incomplete information databases
ACM Transactions on Database Systems (TODS)
Invariant characters of information systems under some homomorphisms
Information Sciences—Informatics and Computer Science: An International Journal
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets in Knowledge Discovery 2: Applications, Case Studies, and Software Systems
Rough Sets in Knowledge Discovery 2: Applications, Case Studies, and Software Systems
A Generalized Definition of Rough Approximations Based on Similarity
IEEE Transactions on Knowledge and Data Engineering
Boolean Reasoning for Decision Rules Generation
ISMIS '93 Proceedings of the 7th International Symposium on Methodologies for Intelligent Systems
International Journal of Approximate Reasoning
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
Converse approximation and rule extraction from decision tables in rough set theory
Computers & Mathematics with Applications
On the evaluation of the decision performance of an incomplete decision table
Data & Knowledge Engineering
Consistency measure, inclusion degree and fuzzy measure in decision tables
Fuzzy Sets and Systems
A rough set approach to the discovery of classification rules in spatial data
International Journal of Geographical Information Science
Applying Rough Sets to Data Tables Containing Missing Values
RSEISP '07 Proceedings of the international conference on Rough Sets and Intelligent Systems Paradigms
Applying Rough Sets to Information Tables Containing Probabilistic Values
MDAI '07 Proceedings of the 4th international conference on Modeling Decisions for Artificial Intelligence
Credible rules in incomplete decision system based on descriptors
Knowledge-Based Systems
Knowledge structure, knowledge granulation and knowledge distance in a knowledge base
International Journal of Approximate Reasoning
Information Sciences: an International Journal
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
Rough Sets under Non-deterministic Information
RSKT '09 Proceedings of the 4th International Conference on Rough Sets and Knowledge Technology
A Study on the Driving Forces of Urban Expansion Using Rough Sets
ICCSA '09 Proceedings of the International Conference on Computational Science and Its Applications: Part I
Handling Spatial-Correlated Attribute Values in a Rough Set
ICCSA '09 Proceedings of the International Conference on Computational Science and Its Applications: Part I
Dominance-based rough set approach to incomplete interval-valued information system
Data & Knowledge Engineering
Topological solution of missing attribute values problem in incomplete information tables
Information Sciences: an International Journal
Rough Set Approximations Based on Granular Labels
RSFDGrC '09 Proceedings of the 12th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing
MGRS: A multi-granulation rough set
Information Sciences: an International Journal
Rough set approach under dynamic granulation in incomplete information systems
MICAI'07 Proceedings of the artificial intelligence 6th Mexican international conference on Advances in artificial intelligence
A granular evolutionary algorithm based on cultural evolution
ISICA'07 Proceedings of the 2nd international conference on Advances in computation and intelligence
RSKT'08 Proceedings of the 3rd international conference on Rough sets and knowledge technology
Approximation reduction in inconsistent incomplete decision tables
Knowledge-Based Systems
Applying rough sets to information tables containing possibilistic values
Transactions on computational science II
Research on rough set theory and applications in China
Transactions on rough sets VIII
Approaches to attribute reduction in concept lattices induced by axialities
Knowledge-Based Systems
Rough set approximations in formal concept analysis
Transactions on rough sets XII
Indiscernibility and similarity in an incomplete information table
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
Dual rough approximations in information tables with missing values
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
RSKT'06 Proceedings of the First international conference on Rough Sets and Knowledge Technology
Knowledge reduction in incomplete information systems based on dempster-shafer theory of evidence
RSKT'06 Proceedings of the First international conference on Rough Sets and Knowledge Technology
A dissimilarity measure for the k-Modes clustering algorithm
Knowledge-Based Systems
A two-grade approach to ranking interval data
Knowledge-Based Systems
ICMLC'05 Proceedings of the 4th international conference on Advances in Machine Learning and Cybernetics
On the local reduction of information system
ICMLC'05 Proceedings of the 4th international conference on Advances in Machine Learning and Cybernetics
Set-valued information systems
Information Sciences: an International Journal
Axiomatic approach of knowledge granulation in information system
AI'06 Proceedings of the 19th Australian joint conference on Artificial Intelligence: advances in Artificial Intelligence
A variable muitlgranulation rough sets approach
ICIC'11 Proceedings of the 7th international conference on Intelligent Computing: bio-inspired computing and applications
Covering based rough set approximations
Information Sciences: an International Journal
Extended rough set-based attribute reduction in inconsistent incomplete decision systems
Information Sciences: an International Journal
Rough set model based on hybrid tolerance relation
RSKT'12 Proceedings of the 7th international conference on Rough Sets and Knowledge Technology
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 selection based on a new conditional entropy for incomplete decision systems
Knowledge-Based Systems
Rough set approach to incomplete numerical data
Information Sciences: an International Journal
A novel method for attribute reduction of covering decision systems
Information Sciences: an International Journal
Multigranulation decision-theoretic rough sets
International Journal of Approximate Reasoning
Rule acquisition and complexity reduction in formal decision contexts
International Journal of Approximate Reasoning
A fast feature selection approach based on rough set boundary regions
Pattern Recognition Letters
Mixed feature selection in incomplete decision table
Knowledge-Based Systems
On the topological properties of generalized rough sets
Information Sciences: an International Journal
Pessimistic rough set based decisions: A multigranulation fusion strategy
Information Sciences: an International Journal
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In this paper, the concept of a maximal consistent block is applied to formulate a new approximation to an object set in incomplete information systems with higher level of accuracy. Similar to the method in [Inform. Sci. 112 (1998) 39, 113 (1999) 271], the proposed rough-set-based rule acquisition method does not require change in the size of the original incomplete system. It, however, has the additional advantage of using a set of simpler discernibility functions of an incomplete system. This means that it can provide a more efficient computation for knowledge acquisition, especially in large incomplete systems.