Abstract
Some possible treatments of incomplete knowledge in conceptual data representation, data analysis and knowledge acquisition are presented. In particular, some ways of conceptual scalings as well as the role of the three-valued Kleene-logic are briefly investigated. This logic is also one background in attribute exploration, a conceptual tool for knowledge acquisition. For this method a strategy is given to obtain as much of (attribute) implicational knowledge about a given “universe” as possible; and we show how to represent incomplete knowledge in order to be able to pin down the questions still to be answered in order to obtain complete knowledge in this situation.
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Burmeister, P., Holzer, R. (2000). On the Treatment of Incomplete Knowledge in Formal Concept Analysis. In: Ganter, B., Mineau, G.W. (eds) Conceptual Structures: Logical, Linguistic, and Computational Issues. ICCS 2000. Lecture Notes in Computer Science(), vol 1867. Springer, Berlin, Heidelberg. https://doi.org/10.1007/10722280_27
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DOI: https://doi.org/10.1007/10722280_27
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