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“Softer” optimization and control models via fuzzy linguistic quantifiers
Information Sciences, 1984Fuzzy linguistic quantifiers, handled by a fuzzy logic based calculus of linguistically quantified propositions, are used to ''soften'' multicriterion and multistage (control) decision models. Basically, in the former case an optimal option is sought best satisfying, e.g., most, almost all, etc.
Kacprzyk, Janusz, Yager, Ronald R.
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On Linguistic Summarization of Time Series Using Fuzzy Logic with Linguistic Quantifiers
2008We discuss first the concept of a linguistic summary of a time series in the setting proposed by the authors1 and then its extension to cover some additional types of summaries that concern the duration of (partial) trends identified here as straight line segments of a piece-wise linear approximation of a time series.
Kacprzyk, J., Wilbik, A., Zadrozny, S.
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Modeling linguistic probabilities and linguistic quantifiers using interval type-2 fuzzy sets
2013 Joint IFSA World Congress and NAFIPS Annual Meeting (IFSA/NAFIPS), 2013In this paper, we synthesize interval type-2 fuzzy set models of linguistic probability words and linguistic quantifiers by applying the Enhanced Interval Approach to data collected from subjects about those words. We establish some user friendly sub-vocabularies of linguistic probabilities and linguistic modifiers, so that they can be used in advanced
Mohammad Reza Rajati, Jerry M. Mendel
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Control chart for linguistic variables: A method based on the use of linguistic quantifiers
International Journal of Production Research, 1999The paper presents a method for conducting the online control of a production process using control charts based on linguistic variables. The novelty of the method consists of the analysis of sample data without superimposing an arbitrary numerical conversion. An example application is also developed.
FRANCESCHINI F, ROMANO, DANIELE
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Interpretative Model for Linguistic Quantifiers
1985This paper attempts to give a model-theoretical account for the semantics of elementary English sentences (the basic units of the semantic structure of the entire language), as a necessary first step towards a compositional interpretive semantics of all the sentences of the language (see Bellert, 1983, for some applications of this proposal to complex ...
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Antonyms and linguistic quantifiers in fuzzy logic
Fuzzy Sets and Systems, 2001The author deals two important topics: the theory for evaluating linguistic predications and the theory of linguistic quantifiers. Both theories are basic to the development of fuzzy logic in the broader sense, proposed as formalization of natural human reasoning.
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Quantifying linguistic coordination
2012Language has been defined as a social coordination device (Clark 1996) enabling innovative modalities of joint action. However, the exact coordinative dynamics over time and their effects are still insufficiently investigated and quantified. Relying on the data produced in a collective decision task (Bahrami et al 2010, Fusaroli et al.
Fusaroli, Riccardo, Tylén, Kristian
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Book Recommender System Using Fuzzy Linguistic Quantifiers
2017The recommender systems are used to facilitate the users with appropriate choices according to their preferences for various online services. Due to the increasing need, various recommendation systems have been developed including recommendation for music, book, movie, etc.
Shahab Saquib Sohail +2 more
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Operators vs. quantifiers: the view from linguistics
Inquiry, 2018In several publications, Francois Recanati argues that time, world, location, and similar constituents are not arguments of the verb, although they do affect truth conditions.
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Fuzzy Logic with Linguistic Quantifiers in Group Decision Making
1992We present how fuzzy logic with linguistic quantifiers, mainly its calculi of linguistically quantified propositions, can be used in group decision making. Basically, the fuzzy linguistic quantifiers (exemplified bymost, almost all,...) are employed to represent a fuzzy majority which is in many cases closer to a real human perception of the very ...
Fedrizzi, Mario, J. Kacprzyk, H. Nurmi
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