Fuzzy linguistic quantifiers --
intended to model vague quantifying expressions in natural language
like `almost all' or `few' -- have gained importance
as operators for
information aggregation and the fusion of gradual evaluations.
appealing because of their ease-of-use: people are familiar with
these operators, and can apply them
for technical aggregation purposes
in the same way as in
Because of the irregular and rather intangible phenomena it tries to model -- viz, those of imprecision and uncertainty -- fuzzy logic should be particularly specific about its foundations. However, work on mathematical foundations and linguistic justification of fuzzy linguistic quantifiers is scarce. In the paper, we propose a framework for evaluating approaches to fuzzy quantification which relates these to the logico-linguistic theory of generalized quantifiers (TGQ). By reformulating these approaches as fuzzification mechanisms, we can investigate properties of the fuzzification mappings which express important aspects of the meaning of natural language quantifiers.
I. Glöckner and A. Knoll
A Framework for Evaluating Fusion Operators Based on the Theory of Generalized Quantifiers
In Proceedings of the 1999 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI '99), Taipei, Taiwan, Aug. 1999
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