Title :
Degree centrality based on the weighted network
Author :
Wei, Daijun ; Li, Ya ; Zhang, Yajuan ; Deng, Yong
Abstract :
Node centrality has been widely studied in the complex networks. In 2010, the model of node centrality under the weighted network was obtained by Tore Opashl et al. Tie weights and the number of ties were connected with certain proportion by tuning parameter in the model. However, the proportion is random measure. In this paper, the selection standard of the optimal turning parameters is proposed. In the proposed method, the maximum degree centrality of node can be emphasized. The numerical example of weighted network on optimal value selection is used to show the efficiency of the method.
Keywords :
complex networks; network theory (graphs); complex networks; maximum degree centrality; node centrality; optimal tuning parameters; optimal value selection; random measure; weighted network; Complex networks; Computers; Educational institutions; Lifting equipment; Numerical models; Social network services; Tuning; Degree centrality; Tuning parameter; Weighted network;
Conference_Titel :
Control and Decision Conference (CCDC), 2012 24th Chinese
Conference_Location :
Taiyuan
Print_ISBN :
978-1-4577-2073-4
DOI :
10.1109/CCDC.2012.6244633