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Introduction: Machine Learning in a Semiotic Perspective

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Aspects of Automatic Text Analysis

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 209))

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Abstract

In order to introduce vagueness as a proper object of formal-mathematical modeling, Max Black [5] developed the notion of consistency profile. Other than classical logics constrained by the principium exclusi tertii, consistency profiles allow mapping the transition from negative to positive predication to any degree. This enabled Black to provide a framework for the classification of predicates according to their vagueness and ambiguity. In other words: Max Black offered a first approach to distinguishing both types of informational uncertainty in, nevertheless, precise, mathematical terms.

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Mehler, A., Köhler, R. (2007). Introduction: Machine Learning in a Semiotic Perspective. In: Aspects of Automatic Text Analysis. Studies in Fuzziness and Soft Computing, vol 209. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-37522-7_1

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