Functional dependencies in relations with null values
Information Processing Letters
Knowledge acquisition by methods of formal concept analysis
Proceedings of the conference on Data analysis, learning symbolic and numeric knowledge
Attribute exploration with background knowledge
Theoretical Computer Science
On the Equivalence of Database Models
Journal of the ACM (JACM)
Formal Concept Analysis: Mathematical Foundations
Formal Concept Analysis: Mathematical Foundations
On the Treatment of Incomplete Knowledge in Formal Concept Analysis
ICCS '00 Proceedings of the Linguistic on Conceptual Structures: Logical Linguistic, and Computational Issues
Theory of Relational Databases
Theory of Relational Databases
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Attribute exploration is an interactive computer algorithm which helps the expert to get informations about the attribute implications of a formal context. In the part I of this paper (see [H04]) an algorithm for attribute exploration with incomplete knowledge was presented. In this part we prove the main results of the algorithm: At the end of the attribute exploration the expert gets maximal information with respect to his knowledge about the unknown universe: He gets a list of implications which are certainly valid, a list of implications which are possibly valid, a list of counterexamples against the implications which are certainly not valid and a list of fictitious counterexamples against the implications which he answered by "unknown". He only has to check the implications which he answered by "unknown" and if he can decide for each of these implications whether it is valid or not, he gets complete knowledge about the implications of the context.