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An Algorithm for Intermediate Quantifiers and the Graded Square of Opposition Towards Linguistic Description of Data

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 642))

Abstract

The aim of this paper is to apply main theories of fuzzy natural logic together with fuzzy GUHA method for a linguistic characterization of relationships in data. Namely, we utilize the theory of intermediate quantifiers, which provides mathematical interpretation of natural language expressions describing quantity such as “Almost all”, “Few” etc., to describe relationships in data using vague terms that are natural in human expression. We provide an algorithm for computation of truth degrees of expressions containing such quantifiers. Moreover, we discuss some basic properties of intermediate quantifiers (contraries, contradictories, sub-contraries and sub-alterns), which formulate the graded Peterson’s square of opposition, and which can be used to infer new expressions from existing ones.

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Notes

  1. 1.

    Applying of delta connective in this definition we solve the problem \( \vdash \pmb {\lnot }(\forall x)(Bx\pmb {\Rightarrow }Ax)\equiv (\exists x)(Bx\mathop {\pmb { \& }}\nolimits \pmb {\lnot }Ax)\) then \(\mathscr {M}(\pmb {\lnot }\mathbf {A}\not \equiv \mathbf {O})=1\) since \(\mathbf {O}\mathrel {:=}\,(\exists x)(Bx\pmb {\wedge }\pmb {\lnot }Ax)\).

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Acknowledgment

The paper has been supported by the project “LQ1602 IT4Innovations excellence in science”.

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Correspondence to Petra Murinová .

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Murinová, P., Burda, M., Pavliska, V. (2018). An Algorithm for Intermediate Quantifiers and the Graded Square of Opposition Towards Linguistic Description of Data. In: Kacprzyk, J., Szmidt, E., Zadrożny, S., Atanassov, K., Krawczak, M. (eds) Advances in Fuzzy Logic and Technology 2017. EUSFLAT IWIFSGN 2017 2017. Advances in Intelligent Systems and Computing, vol 642. Springer, Cham. https://doi.org/10.1007/978-3-319-66824-6_52

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  • DOI: https://doi.org/10.1007/978-3-319-66824-6_52

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