A personalized feedback mechanism based on bounded confidence learning to support consensus reaching in group decision making
… Since the consistency issue is not the focus of this article, it is … where wk is a non-negative
normalized weight associated to … with the process of improving the consensus level without …
normalized weight associated to … with the process of improving the consensus level without …
An overview on managing additive consistency of reciprocal preference relations for consistency-driven decision making and fusion: Taxonomy and future directions
… information fusion methods are … : consistency improving methods; consistency-based methods
to manage incomplete RPRs; consistency control in consensus decision making methods; …
to manage incomplete RPRs; consistency control in consensus decision making methods; …
Social trust driven consensus reaching model with a minimum adjustment feedback mechanism considering assessments-modifications willingness
… [28] investigated consistency and consensus issues in GDM with … to improve the efficiency
of the consensus reaching process. … Herrera-Viedma, “A personalized feedback mechanism …
of the consensus reaching process. … Herrera-Viedma, “A personalized feedback mechanism …
Adaptive consensus reaching process with hybrid strategies for large-scale group decision making
… We give hybrid feedback strategies to improve the consensus degree. … In this situation,
there is no need to provide personalized recommendations for all of the experts in the sub-group. …
there is no need to provide personalized recommendations for all of the experts in the sub-group. …
Consistency-and consensus-based group decision-making method with incomplete probabilistic linguistic preference relations
… Personal use is permitted, but republication/redistribution requires … introduced the following
normalization method to estimate the … model to improve individual consistency and group …
normalization method to estimate the … model to improve individual consistency and group …
Personalized individual semantics based consensus reaching process for large-scale group decision making with probabilistic linguistic preference relations and …
SP Wan, J Yan, JY Dong - Expert Systems with Applications, 2022 - Elsevier
… IR is used to identify DMs who need to improve consensus. DR … B = L ij p n × n can be
normalized into NPLPR B N = L ij N p n × … In this paper, a consistency-driven optimization model is …
normalized into NPLPR B N = L ij N p n × … In this paper, a consistency-driven optimization model is …
Deep graph matching consensus
… Experimentally, we show that row-wise normalization is … at least 40 images with consistent
orientations for each of its five … do help our consensus stage to improve its performance further, …
orientations for each of its five … do help our consensus stage to improve its performance further, …
The overlapping community-driven feedback mechanism to support consensus in social network group decision making
… driven feedback mechanism for improving consensus in SN-… to minimize the consensus cost
by selecting personalized feedback … being the normalized weight of each pair of subgroups. …
by selecting personalized feedback … being the normalized weight of each pair of subgroups. …
Classical dynamic consensus and opinion dynamics models: A survey of recent trends and methodologies
… methods for modeling the dynamism in consensus reaching. In this regard, developed methods
… classical dynamic models, where time does not play a role in modeling the dynamism, …
… classical dynamic models, where time does not play a role in modeling the dynamism, …
Parameter-free consensus embedding learning for multiview graph-based clustering
… noisy data to improve clustering performance; relation-guided … neighborhood and global
subspace consistency. In a word, … v), and p is an abstract normalized constraint of p. After fusing …
subspace consistency. In a word, … v), and p is an abstract normalized constraint of p. After fusing …