Detecting overlapping communities based on vital nodes in complex networks  被引量:2

Detecting overlapping communities based on vital nodes in complex networks

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作  者:Xingyuan Wang Yu Wang Xiaomeng Qin Rui Li Justine Eustace 王兴元;王宇;秦小蒙;李睿;Justine Eustace(School of Information Science and Technology,Dalian Maritime University;Faculty of Electronic Information and Electrical Engineering,Dalian University of Technology;School of Mathematical Sciences,Dalian University of Technology)

机构地区:[1]School of Information Science and Technology,Dalian Maritime University,Dalian 116026,China [2]Faculty of Electronic Information and Electrical Engineering,Dalian University of Technology,Dalian 116024,China [3]School of Mathematical Sciences,Dalian University of Technology,Dalian 116024,China

出  处:《Chinese Physics B》2018年第10期252-259,共8页中国物理B(英文版)

基  金:Project supported by the National Natural Science Foundation of China(Grant Nos.61672124,61370145,61173183,and 61503375);the Password Theory Project of the 13th Five-Year Plan National Cryptography Development Fund,China(Grant No.MMJJ20170203)

摘  要:Detection of community structures in the complex networks is significant to understand the network structures and analyze the network properties. However, it is still a problem on how to select initial seeds as well as to determine the number of communities. In this paper, we proposed the detecting overlapping communities based on vital nodes algorithm(DOCBVA), an algorithm based on vital nodes and initial seeds to detect overlapping communities. First, through some screening method, we find the vital nodes and then the seed communities through the pretreatment of vital nodes. This process differs from most existing methods, and the speed is faster. Then the seeds will be extended. We also adopt a new parameter of attribution degree to extend the seeds and find the overlapping communities. Finally, the remaining nodes that have not been processed in the first two steps will be reprocessed. The number of communities is likely to change until the end of algorithm. The experimental results using some real-world network data and artificial network data are satisfactory and can prove the superiority of the DOCBVA algorithm.Detection of community structures in the complex networks is significant to understand the network structures and analyze the network properties. However, it is still a problem on how to select initial seeds as well as to determine the number of communities. In this paper, we proposed the detecting overlapping communities based on vital nodes algorithm(DOCBVA), an algorithm based on vital nodes and initial seeds to detect overlapping communities. First, through some screening method, we find the vital nodes and then the seed communities through the pretreatment of vital nodes. This process differs from most existing methods, and the speed is faster. Then the seeds will be extended. We also adopt a new parameter of attribution degree to extend the seeds and find the overlapping communities. Finally, the remaining nodes that have not been processed in the first two steps will be reprocessed. The number of communities is likely to change until the end of algorithm. The experimental results using some real-world network data and artificial network data are satisfactory and can prove the superiority of the DOCBVA algorithm.

关 键 词:complex networks overlapping communities vital nodes seed communities 

分 类 号:O157.5[理学—数学]

 

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