Large-scale group decision-making : state-to-the-art clustering and consensus paths / Su-Min Yu, Zhi-Jiao Du.
2022
HD30.23 .Y8 2022eb
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Title
Large-scale group decision-making : state-to-the-art clustering and consensus paths / Su-Min Yu, Zhi-Jiao Du.
Author
ISBN
9789811678899 (electronic bk.)
9811678898 (electronic bk.)
9789811678882
981167888X
9811678898 (electronic bk.)
9789811678882
981167888X
Published
Singapore : Springer, [2022]
Copyright
©2022
Language
English
Description
1 online resource (xxiv, 178 pages) : illustrations (chiefly color)
Item Number
10.1007/978-981-16-7889-9 doi
Call Number
HD30.23 .Y8 2022eb
Dewey Decimal Classification
658.4/030015118
Summary
This book explores clustering operations in the context of social networks and consensus-reaching paths that take into account non-cooperative behaviors. This book focuses on the two key issues in large-scale group decision-making: clustering and consensus building. Clustering aims to reduce the dimension of a large group. Consensus reaching requires that the divergent individual opinions of the decision makers converge to the group opinion. This book emphasizes the similarity of opinions and social relationships as important measurement attributes of clustering, which makes it different from traditional clustering methods with single attribute to divide the original large group without requiring a combination of the above two attributes. The proposed consensus models focus on the treatment of non-cooperative behaviors in the consensus-reaching process and explores the influence of trust loss on the consensus-reaching process.The logic behind is as follows: firstly, a clustering algorithm is adopted to reduce the dimension of decision-makers, and then, based on the clusters opinions obtained, a consensus-reaching process is carried out to obtain a decision result acceptable to the majority of decision-makers. Graduates and researchers in the fields of management science, computer science, information management, engineering technology, etc., who are interested in large-scale group decision-making and consensus building are potential audience of this book. It helps readers to have a deeper and more comprehensive understanding of clustering analysis and consensus building in large-scale group decision-making. .
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Includes bibliographical references.
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text file PDF
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Table of Contents
Chapter 1. Introduction
Chapter 2. Preliminary Knowledge
Chapter 3. Trust-Similarity Analysis-Based Clustering Method
Chapter 4. Trust-Similarity Measure-Based Hierarchical Clustering Method
Chapter 5. Hierarchical Punishment-Driven Consensus Model for Probabilistic Linguistic LSGDM
Chapter 6. Confidence Consensus-Based Model for LSGDM
Chapter 7. Integration of Independent and Supervised Consensus Models
Chapter 8. Consensus Building: Coordination Between Trust Relationships and Opinion Similarity
Chapter 9. Conclusions and Future Research Directions. .
Chapter 2. Preliminary Knowledge
Chapter 3. Trust-Similarity Analysis-Based Clustering Method
Chapter 4. Trust-Similarity Measure-Based Hierarchical Clustering Method
Chapter 5. Hierarchical Punishment-Driven Consensus Model for Probabilistic Linguistic LSGDM
Chapter 6. Confidence Consensus-Based Model for LSGDM
Chapter 7. Integration of Independent and Supervised Consensus Models
Chapter 8. Consensus Building: Coordination Between Trust Relationships and Opinion Similarity
Chapter 9. Conclusions and Future Research Directions. .