A k-core decomposition-based opinion leaders identifying method and clustering-based consensus model for large-scale group decision making
A k-core decomposition-based opinion leaders identifying method and clustering-based consensus model for large-scale group decision making
复制标题
基于k核分解的意见领袖识别方法和基于聚类的大规模群体决策共识模型
DOI：
10.1016/j.cie.2020.106842
复制
发表时间：
2020-12-01
影响因子：
7.9
通讯作者：
Xu, Yejun
中科院分区：
文献类型：
--
作者：
Gao, Pengqun;Huang, Jing;Xu, Yejun
Due to the development of network technology, large-scale group decision making (LSGDM) has become increasingly concerned. In this paper, a k-core decomposition-based opinion leaders identifying method and clustering-based consensus model are developed for LSGDM problems. Firstly, a clustering method based on similarity degree is provided for dividing decision makers (DMs) into several clusters. Then, sub-clusters are presented for social networks (SNs) construction process, which are consist of DMs with same alternative ranking information. Furthermore, a novel k-core decomposition-based opinion leaders identifying method is proposed for selecting opinion leaders of these SNs. Finally, the opinion leaders identified are applied to the following clustering-based consensus model in LSGDM. The weights of DMs are distributed appropriately and the group can efficiently reach a consensus based on the proposed social network analysis (SNA) methods and consensus reaching process (CRP). A case study on flood disaster management shows that the proposed methods are feasible for LSGDM problems.
