The problem of linguistic approximation in clinical decision making
International Journal of Approximate Reasoning
Benchmarking in linguistic importance weighted aggregations
Fuzzy Sets and Systems
Linguistic decision analysis: steps for solving decision problems under linguistic information
Fuzzy Sets and Systems - Special issue on soft decision analysis
On the instantiation of possibility distributions
Fuzzy Sets and Systems
A framework for linguistic modelling
Artificial Intelligence
Multiattribute Preference Analysis with Performance Targets
Operations Research
Linguistic group decision-making: opinion aggregation and measures of consensus
Fuzzy Optimization and Decision Making
A causal analytical method for group decision-making under fuzzy environment
Expert Systems with Applications: An International Journal
Uncertainty modelling for vague concepts: A prototype theory approach
Artificial Intelligence
Linguistic modelling based on semantic similarity relation among linguistic labels
Fuzzy Sets and Systems
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A satisfactory-oriented approach to multiexpert decision-making with linguistic assessments
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A Collective Decision Model Involving Vague Concepts and Linguistic Expressions
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A linguistic modeling of consensus in group decision making basedon OWA operators
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
A consensus model for multiperson decision making with different preference structures
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
A 2-tuple fuzzy linguistic representation model for computing with words
IEEE Transactions on Fuzzy Systems
A new version of 2-tuple fuzzy linguistic representation model for computing with words
IEEE Transactions on Fuzzy Systems
Environmental Modelling & Software
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The main objective of linguistic multi-expert decision making (MEDM) is to select the best alternative(s) using linguistic judgements provided by multiple experts. This paper presents a probabilistic model for linguistic MEDM, which is able to deal with semantic overlapping in linguistic aggregation and decision-makers' preference information in choice function. In linguistic aggregation phase, the vagueness of each linguistic judgement is captured by a possibility distribution on a set of linguistic labels. A confidence parameter is also incorporated into the basic model to model experts' confidence degree. The basic idea of this linguistic aggregation is to transform a possibility distribution into its associated probability distribution. The proposed linguistic aggregation results in a set of labels having a probability distribution. As a choice function, a target-oriented ranking method is proposed, which implies that the decision-maker is satisfactory to choose an alternative as the best if its performance is as at least ''good'' as his requirements. A comparative analysis with prior research is also given to show the advantages of our model via an example borrowed from the literature. The main advantage of our model is its capacity to deal with linguistic labels having partial semantic overlapping as well as incorporate experts and decision-makers' preferences.