1992
DOI: 10.1002/int.4550070105
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Linguistic modifiers and imprecise categories

Abstract: We study knowledge-based systems using fuzzy logic and we focus on the representation of knowledge through linguistic variables characterized by means of fuzzy qualifications or labels. We study a new form of linguistic modifier which slightly changes the qualifications through either a weakening or a reinforcement. This modifier is an important tool for approximate reasoning for two reasons: its use is equivalent to a simple rule given in a symbolic way, avoiding computations and compatible with the fuzzy log… Show more

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Cited by 72 publications
(26 citation statements)
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“…For instance, "very cheap" is more restrictive than "cheap" and "fairly high" is less demanding than "high". The meaning of the predicate "mod P" (where "mod" is a modifier) may be defined in a compositional way and different approaches have been advocated, among which: mod P (x) = ( P (x)) n (see [4]). …”
Section: Reminders About Fuzzy Predicates and Queriesmentioning
confidence: 99%
“…For instance, "very cheap" is more restrictive than "cheap" and "fairly high" is less demanding than "high". The meaning of the predicate "mod P" (where "mod" is a modifier) may be defined in a compositional way and different approaches have been advocated, among which: mod P (x) = ( P (x)) n (see [4]). …”
Section: Reminders About Fuzzy Predicates and Queriesmentioning
confidence: 99%
“…We now wish to divide the linguistic terms into three groups recognized as a left group, a middle group and a right group. Albeit the trials of generating membership functions with modifiers for linguistic terms were already accomplished [1,6], we propose the authors' own procedure of adopting parametric sfunctions whose derivations can be followed in [9][10][11].…”
Section: Creation Of Numerical Expressions For Utilitiesmentioning
confidence: 99%
“…Each fuzzy variable can be associated with adverbs called hedges, which are terms that modify the shape of fuzzy sets. Hedges have two primary behaviors: reinforcement, such as "very", or weakening, such as "little" (Bouchon-Meunier & Yao, 1992).…”
Section: Fuzzy Predicates In Cnf and Dnfmentioning
confidence: 99%