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Managing Group Decision Making criteria values using Fuzzy Ontologies
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Consensus-Based Decision Support Model and Fusion Architecture for Dynamic Decision Making
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In: Electrical and Computer Engineering Publications (2022)
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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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The risk assessment of construction project investment based on prospect theory with linguistic preference orderings
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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-based approach for large scale failure mode and effect analysis with incomplete preference information
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Consensus and opinion evolution-based failure mode and effect analysis approach for reliability management in social network and uncertainty contexts
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Using Multi-granular Fuzzy Linguistic Modelling Methods to Represent Social Networks Related Information in an Organized Way
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A comparison between Fuzzy Linguistic RFM Model and traditional RFM model applied to Campaign Management. Case study of retail business.
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Trust Based Fuzzy Linguistic Recommender Systems as Reinforcement for Personalized Education in the Field of Oral Surgery and Implantology
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Dealing with incomplete information in linguistic group decision making by means of Interval Type‐2 Fuzzy Sets
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In: ISSN: 0884-8173 ; EISSN: 1098-111X ; International Journal of Intelligent Systems ; https://www.hal.inserm.fr/inserm-03026626 ; International Journal of Intelligent Systems, Wiley, 2019, 34 (6), pp.1261-1280. ⟨10.1002/int.22095⟩ (2019)
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Dealing with Incomplete Information in Linguistic Group Decision Making by Means of Interval Type-2 Fuzzy Sets
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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. ; Nowadays in the social network based decision making processes, as the ones involved in e-commerce and e-democracy, multiple users with di erent backgrounds may take part and diverse alternatives might be involved. This diversity enriches the process but at the same time increases the uncertainty in the opinions. This uncertainty can be considered from two di erent perspectives: (i) the uncertainty in the meaning of the words given as preferences, that is motivated by the heterogeneity of the decision makers, (ii) the uncertainty inherent to any decision making process that may lead to an expert not being able to provide all their judgments. The main objective of this contribution is to address these two type of uncertainty. To do so the following approaches are proposed: Firstly, in order to capture, process and keep the uncertainty in the meaning of the linguistic assumption the Interval Type 2 Fuzzy Sets are introduced as a way to model the experts linguistic judgments. Secondly, a measure of the coherence of the information provided by each decision maker is proposed. Finally, a consistency based completion approach is introduced to deal with the uncertainty presented in the expert judgments. The proposed approach is tested in an e-democracy decision making scenario.
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Keyword:
; consistency; e-democracy; Group decision making; Incomplete information; Interval type 2 fuzzy sets; Linguistic preference relations; Uncertainty
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URL: https://doi.org/10.1002/int.22095 http://hdl.handle.net/2086/17489
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A risk-aware fuzzy linguistic knowledge-based recommender system for hedge funds
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Expanding Grey Relational Analysis With the Comparable Degree for Dual Probabilistic Multiplicative Linguistic Term Sets and Its Application on the Cloud Enterprise
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A Fuzzy Linguistic RFM Model Applied to Campaign Management
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Using clustering methods to deal with high number of alternatives on Group Decision Making
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An overview on managing additive consistency of reciprocal preference relations for consistency-driven decision making and Fusion: Taxonomy and future directions
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