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Consistency-driven methodology to manage incomplete linguistic preference relation: A perspective based on personalized individual semantics
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Consistency improvement with a feedback recommendation in personalized linguistic group decision making
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Abstract:
The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link. ; Consistency is an important issue in linguistic decision making with various consistency measures and consistency improving methods available in the literature. However, existing linguistic consistency studies omit the fact that words mean different things for different people, that is, decision makers' personalized individual semantics (PISs) over their expressed linguistic preferences are ignored. Therefore, the aim of this article is to propose a novel consistency improving approach based on PISs in linguistic group decision making. The proposed approach combines the characteristics of personalized representation and integrates the PIS-based model in measuring and improving the consistency of linguistic preference relations. A detailed numerical and comparative analysis to support the feasibility of the proposed approach is provided.
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Keyword:
Additives; Computational modeling; Decision making; Linguistics; Numerical models; Semantics
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URL: https://dora.dmu.ac.uk/handle/2086/21231 https://doi.org/10.1109/tcyb.2021.3085760
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Consistency Improvement With a Feedback Recommendation in Personalized Linguistic Group Decision Making
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Distributed Linguistic Representations in Decision Making: Taxonomy, Key Elements and Applications, and Challenges in Data Science and Explainable Artificial Intelligence ...
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Revisiting Fuzzy and Linguistic Decision-Making: Scenarios and Challenges for Wiser Decisions in a Better Way
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Personalized individual semantics in computing with words for supporting linguistic group decision making
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Personalized individual semantics in Computing with Words for supporting linguistic Group Decision Making. An Application on Consensus reaching
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