On the specificity of a possibility distribution
Fuzzy Sets and Systems
Handbook of logic in artificial intelligence and logic programming (vol. 3)
Rough-set reasoning about uncertain data
Fundamenta Informaticae - Special issue: rough sets
On Databases with Incomplete Information
Journal of the ACM (JACM)
Intelligent systems and interfaces
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
A Logical Approach to Fuzzy Data Analysis
PKDD '99 Proceedings of the Third European Conference on Principles of Data Mining and Knowledge Discovery
Reducing Information Systems with Uncertain Attributes
ISMIS '96 Proceedings of the 9th International Symposium on Foundations of Intelligent Systems
A Generalized Decision Logic in Interval-Set-Valued Information Tables
RSFDGrC '99 Proceedings of the 7th International Workshop on New Directions in Rough Sets, Data Mining, and Granular-Soft Computing
Fuzzy logic = computing with words
IEEE Transactions on Fuzzy Systems
RSFDGrC'05 Proceedings of the 10th international conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing - Volume Part I
Arrow decision logic for relational information systems
Transactions on Rough Sets V
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In this paper, we investigate a knowledge representation formalism in the context of fuzzy data tables. A possibilistic decision logic incorporating linguistic terms is proposed for representing and reasoning about knowledge in fuzzy data tables. Two applications based on the logic are described. The first is the extraction of fuzzy rules from general fuzzy data tables. In this application, the knowledge in the tables may be made explicit by the formulas of the logic or used implicitly in decision-making. The second is for the fuzzy quantization problem of precise data tables. It can be viewed as a special case of the first, however, due to some special properties of the problem, a polynomial time rule extraction process can be obtained. Finally, the relationship of the logic with some works for handling uncertain information in data tables is also discussed.