DocumentCode :
3767452
Title :
Computing Unbalanced Degree of Signed Networks Based on Culture Algorithm
Author :
Xiaohui Zhao;Fangai Liu;Yongxin Zhang;Jiwei Wang
Author_Institution :
Sch. of Math. Sci., Shandong Normal Univ., Jinan, China
fYear :
2015
Firstpage :
305
Lastpage :
312
Abstract :
Signed network is the network with both positive and negative links. Many real-world complex systems can be represented as signed networks, which are unbalanced according to structural balance theory. Unbalanced degree of signed networks is the distance to exact balance. Evaluating unbalanced degree of signed networks is a NP-hard problem, which has attracted many attentions. Many approaches are developed to compute structural balance. However, the results obtained by these approaches are unsatisfactory. In this study, the computation of unbalanced degree is convert to an optimization problem whose object function is come from the Hamiltonian of Edwards-Anderson spin glass model. We use a new Cultural Algorithm named CA-SNB to solve the optimization problem. The Cultural Algorithm, a new computable framework of Evolution Algorithm, has been successfully applied to many areas. In CA-SNB, the evolution of population space and belief space is based on Genetic Algorithm and greedy strategy respectively. Experiments on social and biological networks show the excellent effectiveness and efficiency of the proposed method.
Keywords :
"Sociology","Statistics","Cultural differences","Linear programming","Glass","Algorithm design and analysis","Social network services"
Publisher :
ieee
Conference_Titel :
Cloud Computing and Big Data (CCBD), 2015 International Conference on
Type :
conf
DOI :
10.1109/CCBD.2015.31
Filename :
7450567
Link To Document :
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