Tolerance approximation spaces
Fundamenta Informaticae - Special issue: rough sets
Extensions and intentions in the rough set theory
Information Sciences: an International Journal
Relational interpretations of neighborhood operators and rough set approximation operators
Information Sciences—Informatics and Computer Science: An International Journal
Rules in incomplete information systems
Information Sciences: an International Journal
Neighborhood systems and relational databases
CSC '88 Proceedings of the 1988 ACM sixteenth annual conference on Computer science
A Generalized Definition of Rough Approximations Based on Similarity
IEEE Transactions on Knowledge and Data Engineering
Reduction and axiomization of covering generalized rough sets
Information Sciences: an International Journal
On decomposition for incomplete data
Fundamenta Informaticae
Constructive and axiomatic approaches of fuzzy approximation operators
Information Sciences—Informatics and Computer Science: An International Journal - Mining stream data
Mining diagnostic rules from clinical databases using rough sets and medical diagnostic model
Information Sciences: an International Journal - Special issue: Medical expert systems
Information-preserving hybrid data reduction based on fuzzy-rough techniques
Pattern Recognition Letters
Topological approaches to covering rough sets
Information Sciences: an International Journal
Knowledge reduction based on the equivalence relations defined on attribute set and its power set
Information Sciences: an International Journal
Information Sciences: an International Journal
Measuring roughness of generalized rough sets induced by a covering
Fuzzy Sets and Systems
Measures for evaluating the decision performance of a decision table in rough set theory
Information Sciences: an International Journal
Expert Systems with Applications: An International Journal
Dominance-based rough set approach and knowledge reductions in incomplete ordered information system
Information Sciences: an International Journal
Rough set theory for the interval-valued fuzzy information systems
Information Sciences: an International Journal
Maximal consistent extensions of information systems relative to their theories
Information Sciences: an International Journal
Fuzzy rough set theory for the interval-valued fuzzy information systems
Information Sciences: an International Journal
Generalized fuzzy rough sets determined by a triangular norm
Information Sciences: an International Journal
Attribute reduction in decision-theoretic rough set models
Information Sciences: an International Journal
Generalized rough sets based on reflexive and transitive relations
Information Sciences: an International Journal
Relationship between generalized rough sets based on binary relation and covering
Information Sciences: an International Journal
A new measure of uncertainty based on knowledge granulation for rough sets
Information Sciences: an International Journal
Discernibility matrix simplification for constructing attribute reducts
Information Sciences: an International Journal
Approaches to knowledge reduction of covering decision systems based on information theory
Information Sciences: an International Journal
Constructive and algebraic methods of the theory of rough sets
Information Sciences: an International Journal
Information Sciences: an International Journal
The superiority of three-way decisions in probabilistic rough set models
Information Sciences: an International Journal
On lower and upper intension order relations by different cover concepts
Information Sciences: an International Journal
The ϑ-lower and T-upper fuzzy rough approximation operators on a semigroup
Information Sciences: an International Journal
Generalized intuitionistic fuzzy rough sets based on intuitionistic fuzzy coverings
Information Sciences: an International Journal
Rough set theory applied to lattice theory
Information Sciences: an International Journal
Covering based rough set approximations
Information Sciences: an International Journal
An application of rough sets to graph theory
Information Sciences: an International Journal
Topological characterizations of covering for special covering-based upper approximation operators
Information Sciences: an International Journal
Relationships among generalized rough sets in six coverings and pure reflexive neighborhood system
Information Sciences: an International Journal
Information Sciences: an International Journal
Rough set model based on formal concept analysis
Information Sciences: an International Journal
The necessary and sufficient conditions for a fuzzy relation being Τ-Euclidean
Information Sciences: an International Journal
Some properties of generalized rough sets
Information Sciences: an International Journal
Similarity and dissimilarity measures between fuzzy sets: A formal relational study
Information Sciences: an International Journal
Related family: A new method for attribute reduction of covering information systems
Information Sciences: an International Journal
Multigranulation rough sets: From partition to covering
Information Sciences: an International Journal
Approximation operators on complete completely distributive lattices
Information Sciences: an International Journal
A novel method for attribute reduction of covering decision systems
Information Sciences: an International Journal
International Journal of Approximate Reasoning
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The notion of rough sets was originally proposed by Pawlak. In Pawlak's rough set theory, the equivalence relation or partition plays an important role. However, the equivalence relation or partition is restrictive for many applications because it can only deal with complete information systems. This limits the theory's application to a certain extent. Therefore covering-based rough sets are derived by replacing the partitions of a universe with its coverings. This paper focuses on the further investigation of covering-based rough sets. Firstly, we discuss the uncertainty of covering in the covering approximation space, and show that it can be characterized by rough entropy and the granulation of covering. Secondly, since it is necessary to measure the similarity between covering rough sets in practical applications such as pattern recognition, image processing and fuzzy reasoning, we present an approach which measures these similarities using a triangular norm. We show that in a covering approximation space, a triangular norm can induce an inclusion degree, and that the similarity measure between covering rough sets can be given according to this triangular norm and inclusion degree. Thirdly, two generalized covering-based rough set models are proposed, and we employ practical examples to illustrate their applications. Finally, relationships between the proposed covering-based rough set models and the existing rough set models are also made.