Conceptual structures: information processing in mind and machine
Conceptual structures: information processing in mind and machine
Foundations of cognitive science
The hierarchies of knowledge and the mathematics of discovery
Minds and Machines
The rough sets theory and evidence theory
Fundamenta Informaticae
Constructive and algebraic methods of the theory of rough sets
Information Sciences: an International Journal
Attribute reduction in concept lattice based on discernibility matrix
RSFDGrC'05 Proceedings of the 10th international conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing - Volume Part II
Concept granular computing systems
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 1
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From the classic view in which a concept consists of the set of extents and the set of intents, a concept learning system extended from a formal context is introduced and two concepts such as an under concept and an over concept are defined. Any pair of subsets from extents and intents in this concept learning system can be changed to an under or an over concept. Further it can be changed to a concept by learning from the set of extents or from the set of intents. It is proved that the concept learned in this framework is an optimal concept. This process of learning a concept describes the recognizing ability from unclear to clear.