General multiple-objective decision functions and linguistically quantified statements
International Journal of Man-Machine Studies - Lecture notes in computer science Vol. 174
Database queries with fuzzy linguistic quantifiers
IEEE Transactions on Systems, Man and Cybernetics
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Journal of Symbolic Logic
Cardinality, quantifiers, and the aggregation of fuzzy criteria
Fuzzy Sets and Systems - Special issue on fuzzy information processing
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Artificial Intelligence
Dynamic reasoning with qualified syllogisms
Artificial Intelligence
An overview of fuzzy quantifiers. (I). Interpretations
Fuzzy Sets and Systems
An overview of fuzzy quantifiers (II). Reasoning and applications
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Plausibility measures and default reasoning
Journal of the ACM (JACM)
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Inductive Learning From Incomplete and Imprecise Examples
IPMU '90 Proceedings of the 3rd International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems: Uncertainty in Knowledge Bases
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A framework for linguistic modelling
Artificial Intelligence
Plausibility measures: a user's guide
UAI'95 Proceedings of the Eleventh conference on Uncertainty in artificial intelligence
Fuzzy logic = computing with words
IEEE Transactions on Fuzzy Systems
Perturbation of fuzzy reasoning
IEEE Transactions on Fuzzy Systems
Implication operators in fuzzy logic
IEEE Transactions on Fuzzy Systems
A formal model of computing with words
IEEE Transactions on Fuzzy Systems
A framework for fuzzy quantification models analysis
IEEE Transactions on Fuzzy Systems
Linguistic quantifiers based on Choquet integrals
International Journal of Approximate Reasoning
Prenex normal form in linguistic quantifiers modeled by Sugeno integrals
Fuzzy Sets and Systems
Information Sciences: an International Journal
L-fuzzy quantifiers of type determined by fuzzy measures
Fuzzy Sets and Systems
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Since quantifiers have the ability of summarizing the properties of a class of objects without enumerating them, linguistic quantification is a very important topic in the field of high level knowledge representation and reasoning. This paper introduces a new framework for modeling quantifiers in natural languages in which each linguistic quantifier is represented by a family of fuzzy measures, and the truth value of a quantified proposition is evaluated by using Sugeno's integral. This framework allows us to have some elegant logical properties of linguistic quantifiers. We compare carefully our new model of quantification and other approaches to linguistic quantifiers. A set of criteria for linguistic quantification was proposed in the previous literature. The relationship between these criteria and the results obtained in the present paper is clarified. Some simple applications of the Sugeno's integral semantics of quantifiers are presented.