This paper introduces a semantic model for vague quantifiers (VQs) combining Fuzzy Theory (FT) and Supervaluation Theory (ST), which are the two main theories on vagueness, a common source of uncertainty in natural language. After comparing FT and ST, I will develop the desired model and a numerical method for evaluating truth values of vague quantified statements, called the Modified Glöckner's Method, that combines the merits and overcomes the demerits of the two theories. I will also show how the model can be applied to evaluate truth values of complex quantified statements with iterated VQs. © 2011 Springer-Verlag.
CITATION STYLE
Chow, K. F. (2011). A semantic model for vague quantifiers combining fuzzy theory and supervaluation theory. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6953 LNAI, pp. 61–73). https://doi.org/10.1007/978-3-642-24130-7_4
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