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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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Consistency Improvement With a Feedback Recommendation in Personalized Linguistic Group Decision Making
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Abstract:
This work was supported in part by the NSF of China under Grant 71901182, Grant 71601133, and Grant 71871149; in part by Sichuan University under Grant sksyl201705 and Grant YJ201906; in part by Southwest Jiaotong University under Grant YJSY-DSTD201918; in part by the China Postdoctoral Science Foundation under Grant 2020M673283 and Grant 2682021ZTPY073; and in part by the Spanish State Research Agency under Project PID2019-103880RB-I00/AEI/10.13039/501100011033. ; 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. ; National Natural Science Foundation of China (NSFC) 71901182 71601133 71871149 ; Sichuan University sksyl201705 YJ201906 ; Southwest Jiaotong University YJSY-DSTD201918 ; China Postdoctoral Science Foundation 2020M673283 2682021ZTPY073 ; Spanish Government PID2019-103880RB-I00
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Keyword:
Consistency; Group decision making (GDM); Linguistic preference relation; Personalized individual semantics (PISs)
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URL: http://hdl.handle.net/10481/72452 https://doi.org/10.1109/TCYB.2021.3085760
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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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