Fuzzy nodes recognition based on spectral clustering in complex networks

被引：10
作者：
Ma, Yang [1 ]
Cheng, Guangquan [1 ]
Liu, Zhong [1 ]
Xie, Fuli [1 ]
机构：
[1] Natl Univ Def Technol, Sci & Technol Informat Syst Engn Lab, Changsha 410073, Hunan, Peoples R China
来源：
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS | 2017年 / 465卷
基金：
国家教育部博士点专项基金资助; 中国国家自然科学基金;
关键词：
Complex network; Network reconstruction; Fuzzy nodes; Spectral clustering; LINK PREDICTION;
D O I：
10.1016/j.physa.2016.08.022
中图分类号：
O4 [物理学];
学科分类号：
0702 ;
摘要：
In complex networks, information regarding the nodes is usually incomplete because of the effects of interference, noise, and other factors. This results in parts of the network being blurred and some information having an unknown source. In this paper, a spectral clustering algorithm is used to identify fuzzy nodes and solve network reconstruction problems. By changing the fuzzy degree of placeholders, we achieve various degrees of credibility and accuracy for the restored network. Our approach is verified by experiments using open source datasets and simulated data. (C) 2016 Elsevier B.V. All rights reserved.
引用
收藏
页码：792 / 797
页数：6
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