Large-Scale Group Decision-Making: State-to-the-Art Clustering and Consensus Paths

This book explores clustering operations in social networks and consensus-reaching paths considering non-cooperative behaviors. It focuses on large-scale group decision-making, addressing clustering and consensus building. Clustering reduces dimension, while consensus reaching requires convergent opinions. The book emphasizes the similarity of opinions and social relationships as key attributes. Consensus models consider non-cooperative behaviors and the impact of trust loss. It is suitable for graduates and researchers in management science, computer science, and related fields.

Format: Paperback / softback
Length: 179 pages
Publication date: 05 January 2023
Publisher: Springer Verlag, Singapore

This comprehensive book delves into the realm of clustering operations within the context of social networks, taking into account the influence of non-cooperative behaviors on consensus-reaching paths. It specifically focuses on two critical aspects of large-scale group decision-making: clustering and consensus building. Clustering aims to reduce the dimensionality of a large group, while consensus reaching necessitates the convergence of divergent individual opinions into a collective group opinion.

What sets this book apart is its emphasis on the similarity of opinions and social relationships as key measurement attributes of clustering. Unlike traditional clustering methods that rely solely on a single attribute to divide the original large group, the proposed consensus models incorporate both attributes to achieve effective division. This approach allows for a more comprehensive understanding of the dynamics within the group and facilitates the attainment of consensus.

The book's proposed consensus models specifically address the treatment of non-cooperative behaviors in the consensus-reaching process. It explores the impact of trust loss on the consensus-reaching process and offers insights into strategies for mitigating its effects. By employing a clustering algorithm to reduce the dimensionality of decision-makers, the book facilitates the subsequent consensus-reaching process, leading to a decision result that is acceptable to the majority of decision-makers.

This book is of immense value to graduates and researchers in the fields of management science, computer science, information management, engineering technology, and related disciplines. It provides a deep and comprehensive understanding of clustering analysis and consensus building in large-scale group decision-making, enabling readers to apply these principles to real-world scenarios and contribute to the advancement of this field.

Weight: 320g
Dimension: 235 x 155 (mm)
ISBN-13: 9789811678912
Edition number: 1st ed. 2022