Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Mathematical Foundations
Rough Sets: Mathematical Foundations
Granular Computing and Rough Set Theory
RSEISP '07 Proceedings of the international conference on Rough Sets and Intelligent Systems Paradigms
Approximation Theories: Granular Computing vs Rough Sets
RSCTC '08 Proceedings of the 6th International Conference on Rough Sets and Current Trends in Computing
On generalizing rough set theory
RSFDGrC'03 Proceedings of the 9th international conference on Rough sets, fuzzy sets, data mining, and granular computing
Covering rough sets based on neighborhoods: An approach without using neighborhoods
International Journal of Approximate Reasoning
Approximation spaces and information granulation
Transactions on Rough Sets III
CMC'12 Proceedings of the 13th international conference on Membrane Computing
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In the present paper a logically exact way is presented in order to define approximative functors on object level in the partial first-order logic relying on approximation spaces. By the help of defined approximative functors one can determine what kind of approximations has to be taken into consideration in the evaluating process of a formula. The representations of concepts (properties) of our available knowledge can be used to approximate not only any concept (property) but any relation. In the last section lower and upper characteristic matrixes are introduced. These can be very useful in different applications.