A Probe Into Semantic Fuzziness

Natural languages are abundant in the use of fuzzy expressions, and fuzziness like precision is one of the characteristics of natural languages. The present author points out that the classical semantic theory cannot fulfill the task of dealing with semantic fuzziness. Whereas, Zadeh's fuzzy set theory in terms of membership provides an effective platform in dealing with numerous fuzzy linguistic phenomena. This thesis in the light of fuzzy set theory makes an initial probe into semantic fuzziness.The nature of fuzziness is its unsharp referential boundary, it is the essence that acts as the major criterion in distinguishing fuzziness from generality, ambiguity, and vagueness. Fuzziness is inherent in the sense that it has no clear-cut referential boundary, and is not resolved with resort to context, as opposed to generality, vagueness and ambiguity, which may be contextually removed. An important implication of this is that ultimately ambiguity, generality and vagueness are not as pervasive and important as fuzziness is in the study of meaning.Although the extensional application of fuzziness is indefinite, the kernel part of fuzzy semantics is definite. Fuzziness also features in that precision and fuzziness can mutually transfer to each other in acertain condition, and artificial stipulations cannot remove the fuzziness.Semantic information is hypothesized that was stored up in the cognitive system in form of semantic features which define semantic prototype. Very generally, humans appear to organize items into appropriate categories, of which their boundaries are not fixed, i.e. the sets are fuzzy. In a fuzzy semantic category, prototype acts as a norm in that the closer an atypical item to the prototype, the higher degree of membership it would have. Prototype and loose rule play important parts in comprehension of semantic fuzziness.Semantic fuzziness may be described in a quantitative way by degree of membership. Various conditions and hedges are main factors that influence making out degree of membership.This thesis probes into semantic fuzziness from perspective of natural language and formal language. The theme of this thesis is designed to gain a comprehensive and fresh knowledge of semantic fuzziness in an integral approach combining linguistics, logic, psychology and cognition...