Community Division of Bipartite Network Based on Information Transfer Probability
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    Abstract:

    Bipartite network is a performance of complex networks, the divided of unilateral node of bipartite network has important practical significance for the study of complex networks of community division. Based on the idea of information transfer probability, this paper presents a community of bipartite network divided clustering algorithm (IPS algorithm). The algorithm simulates the probability of information transfer in the network, through mutual support value between the nodes in network.select the max value as the basis for merger different communities and introduction of bipartite network module as a basis for judging the merits of community division. Finally, we using actual network test the performance of the algorithm. Experimental results show that the algorithm can not only accurate divided the unilateral node of bipartite network, but also can get high quality community division.

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张弛,周永刚,范纯龙,唐桂林.基于信息扩散概率的二分网络社区划分算法.计算机系统应用,2015,24(12):239-242

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History
  • Received:April 09,2015
  • Revised:June 11,2015
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  • Online: December 04,2015
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