Attribute exploration with background knowledge
Theoretical Computer Science
Formal Concept Analysis: Mathematical Foundations
Formal Concept Analysis: Mathematical Foundations
ICCS '99 Proceedings of the 7th International Conference on Conceptual Structures: Standards and Practices
Pseudo-models and propositional Horn inference
Discrete Applied Mathematics - Ordinal and symbolic data analysis (OSDA 2000)
Using Formal Concept Analysis in Mathematical Discovery
Calculemus '07 / MKM '07 Proceedings of the 14th symposium on Towards Mechanized Mathematical Assistants: 6th International Conference
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Sometimes even the most elementary data type of Formal Concept Analysis, that of a formal context, can be difficult to handle. This is typically the case when the context under consideration is not fully available, because e.g. it is too large to be completely recorded. Then even the question “Which attribute combinations are possible?” cannot simply be answered by giving all concept intents, because such a list may be huge and therefore of little insight. In such a situation, the weaker information that certain attribute combinations are possible and others are not, may be of interest. A language to systematically address such information was introduced in [8] under the name of “Contextual Attribute Logic”. It activates (with an entirely different semantic in mind) basic notions of mathematical Propositional Logic for the investigations of Formal Concept Analysis.