Study on Community Discovery Algorithm from the Perspection of Label Influence Propagation

Jie Jian, Xiaoming Yu, Jinchi Zhu, Xueyan Liu, Hongtao Liu
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Abstract

In order to better discover the overlapping communities, this paper proposes an overlapping community detection method (INFELPA) based on the influence of the label and the spread of the edge tags. We use the influence of the node to initialize the label on the edge and sort the edge's influence to avoid these random factors during the edge label updating process. In order to retain multiple communities we retain multiple labels on the edges and restore the completed edge tag to the node. The experimental results show that this algorithm has certain competitive advantages
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标签影响传播视角下的社区发现算法研究
为了更好地发现重叠社区,本文提出了一种基于标签影响和边缘标签传播的重叠社区检测方法(INFELPA)。我们利用节点的影响来初始化边缘上的标签,并对边缘的影响进行排序,以避免在边缘标签更新过程中出现这些随机因素。为了保留多个社区,我们在边缘上保留多个标签,并将完成的边缘标签恢复到节点。实验结果表明,该算法具有一定的竞争优势
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