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首页> 外文会议>2019 International Conference on Communications, Information System and Computer Engineering >An Overlapping Community Discovery Algorithm Based on Label Propagation
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An Overlapping Community Discovery Algorithm Based on Label Propagation

机译：基于标签传播的重叠社区发现算法

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Aiming at the defects of random update and poor stability of COPRA algorithm, this paper proposes an overlapping community discovery algorithm based on label propagation (COLBN). The algorithm calculates the value of the node by traversing each node, and finds the reference node to determine the number of divided communities. Then, the reference node is used to update the label for the adjacent node to identify the overlapping node, and the overlapping community can be divided when all overlapping nodes are found. This paper makes use of the network dataset of the bottlenose dolphins in the Magic Bay and the book dataset on American politics, and the comparison test of COPRA algorithm, which proves that the COLBN algorithm significantly reduces the update randomness of the label propagation process and improves the stability of the generated network communities.
机译：针对COPRA算法的随机更新和稳定性差的缺点，提出了一种基于标签传播的重叠社区发现算法。该算法通过遍历每个节点来计算节点的值，并找到参考节点以确定划分的社区数。然后，参考节点用于更新相邻节点的标签以标识重叠节点，并且在找到所有重叠节点时可以对重叠社区进行划分。本文利用魔术湾宽吻海豚的网络数据集和美国政治上的书籍数据集，以及COPRA算法的对比测试，证明了COLBN算法大大降低了标签传播过程的更新随机性，并提高了生成的网络社区的稳定性。

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