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Perceptual Computing: Aiding People in Making Subjective Judgments

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TLDR
Perceptual Computing explains how to implement CWW to aid in the important area of making subjective judgments, using a methodology that propagates random and linguistic uncertainties into the subjective judgment in a way that can be modeled and observed by the judgment maker.
Abstract
Explains for the first time how "computing with words" can aid in making subjective judgments Lotfi Zadeh, the father of fuzzy logic, coined the phrase "computing with words" (CWW) to describe a methodology in which the objects of computation are words and propositions drawn from a natural language. Perceptual Computing explains how to implement CWW to aid in the important area of making subjective judgments, using a methodology that leads to an interactive devicea "Perceptual Computer"that propagates random and linguistic uncertainties into the subjective judgment in a way that can be modeled and observed by the judgment maker. This book focuses on the three components of a Perceptual Computerencoder, CWW engines, and decoderand then provides detailed applications for each. It uses interval type-2 fuzzy sets (IT2 FSs) and fuzzy logic as the mathematical vehicle for perceptual computing, because such fuzzy sets can model first-order linguistic uncertainties whereas the usual kind of fuzzy sets cannot. Drawing upon the work on subjective judgments that Jerry Mendel and his students completed over the past decade, Perceptual Computing shows readers how to: Map word-data with its inherent uncertainties into an IT2 FS that captures these uncertainties Use uncertainty measures to quantify linguistic uncertainties Compare IT2 FSs by using similarity and rank Compute the subsethood of one IT2 FS in another such set Aggregate disparate data, ranging from numbers to uniformly weighted intervals to nonuniformly weighted intervals to words Aggregate multiple-fired IF-THEN rules so that the integrity of word IT2 FS models is preserved Free MATLAB-based software is also available online so readers can apply the methodology of perceptual computing immediately, and even try to improve upon it. Perceptual Computing is an important go-to for researchers and students in the fields of artificial intelligence and fuzzy logic, as well as for operations researchers, decision makers, psychologists, computer scientists, and computational intelligence experts.

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An overview on the 2-tuple linguistic model for computing with words in decision making: Extensions, applications and challenges

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Personalized individual semantics in computing with words for supporting linguistic group decision making. An application on consensus reaching

TL;DR: In this article, a personalized individual semantics (PIS) model is proposed to personalize individual semantics by means of an interval numerical scale and the 2-tuple linguistic model, and a new CW framework is defined, such a CW framework allows us to deal with PIS to facilitate CW keeping the idea that words mean different things to different people.
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Managing consistency and consensus in group decision making with hesitant fuzzy linguistic preference relations

TL;DR: This paper develops separate consistency and consensus processes to deal with HFLPR individual rationality and group rationality and introduces a possibility distribution approach and a 2-tuple linguistic model to aid the consistency improvement process in a given H FLPR.
References
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