Fast extraction of the backbone of projected bipartite networks to aid community detection
Fast extraction of the backbone of projected bipartite networks to aid community detection
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DOI：
10.1209/0295-5075/113/28003
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发表时间：
2016-01-01
期刊：
影响因子：
1.8
通讯作者：
Rao, A.
中科院分区：
文献类型：
--
作者：
Liebig, J.;Rao, A.
本文介绍了一种计算成本低的方法，用于提取从二分网络投影的单模网络的骨干。我们发现，在一个模式的投影的边缘权重分布根据泊松二项分布，并找到预期的权重分布的一个模式的网络从一个随机的二分网络投影只需要知识的二分度分布。能够提取投影的主干非常有利于过滤掉大型复杂网络中的冗余信息，并将单模式投影中的信息缩小到最相关的信息。我们证明了一个模式的投影艾滋病的检测社区的骨干。版权所有（C）2016 EPLA
This paper introduces a computationally inexpensive method for extracting the backbone of one-mode networks projected from bipartite networks. We show that the edge weights in the one-mode projections are distributed according to a Poisson binomial distribution and that finding the expected weight distribution of a one-mode network projected from a random bipartite network only requires knowledge of the bipartite degree distributions. Being able to extract the backbone of a projection is highly beneficial in filtering out redundant information in large complex networks and narrowing down the information in the one-mode projection to the most relevant. We demonstrate that the backbone of a one-mode projection aids in the detection of communities. Copyright (C) EPLA, 2016