Evaluation of quantified propositions in generalized models of fuzzy quantification

被引:18
|
作者
Glöckner, I [1 ]
机构
[1] Fern Univ Hagen, D-58084 Hagen, Germany
关键词
fuzzy quantifier; semi-fuzzy quantifier; quantifier fuzzification mechanism; generalized quantifiers; natural language processing;
D O I
10.1016/j.ijar.2003.09.005
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The quantifiers found in natural language (NL) are not restricted to the absolute and proportional types usually considered in fuzzy set theory. In order to handle the wealth of NL quantifiers including quantifiers of exception ("all except about ten"), cardinal comparatives ("many more than") and others, it is necessary to consider generalized models of fuzzy quantification. Starting from an analysis in terms of semi-fuzzy quantifiers (specifications) and fuzzification mechanisms (prototypical models), the sequel develops a precise notion of generalized models which rests on a formalization of linguistic adequacy criteria. It also presents concrete examples of such models which generalize the FG-count and OWA approaches to fuzzy quantification. In order to let applications profit from the improved coverage and coherence of interpretations, the sequel is especially concerned with the issue of practical implementation. It presents efficient methods for implementing the main types of quantifying propositions which demonstrate the computational feasibility of the proposed models. (C) 2004 Elsevier Inc. All rights reserved.
引用
收藏
页码:93 / 126
页数:34
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