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Inference method for fuzzy quantified and truth qualified natural language propositions

机译:模糊量化和真值自然语言命题的推理方法

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摘要

This paper proposes an inference method for fuzzy quantified and truth qualified natural language proposi- tions. For example, for "Most tall men heavy is true", a modified proposition "Many more or less tall men are heavy is true", can be derived by inference. For the quantified "more or less", the fuzzy quantifier "many" can be derived analytically. Three types of fuzzy quantifiers(the mono- tonically nonincreasing type such as "few, the monotoni- cally nondecreasing type such as "most", and the single-peaked type such as "several"), as well as the mono- tonic and injection type truth quantified qualifier such as true and false, are considered.
机译:本文提出了一种对模糊量化和符合真值的自然语言建议的推理方法。例如,对于“大多数高个子男人沉重是真实的”,可以通过推论得出修改的命题“许多或多个高个子男人沉重是真实的”。对于量化的“或多或少”,可以通过分析得出模糊量词“很多”。三种类型的模糊量词(单调非递增类型,例如“很少”;单调非递减类型,例如“最”;以及单峰类型,例如“几个”),以及单调和考虑使用注入类型真值量化限定符,例如true和false。

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