Consistency Improvement With a Feedback Recommendation in Personalized Linguistic Group Decision Making
Metadatos
Mostrar el registro completo del ítemEditorial
IEEE
Materia
Consistency Group decision making (GDM) Linguistic preference relation Personalized individual semantics (PISs)
Fecha
2021-05-26Referencia bibliográfica
Published version: C.-C. Li... [et al.]. "Consistency Improvement With a Feedback Recommendation in Personalized Linguistic Group Decision Making," in IEEE Transactions on Cybernetics, doi: [10.1109/TCYB.2021.3085760]
Patrocinador
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-I00Resumen
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.