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Dynamic Overlapping Community Discovery Based on Core Nodes

机译:基于核心节点的动态重叠社区发现

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Social networks in the real world are evolutionary and large scale. Detecting the community structure could express the structure and characteristics of complex networks effectively. Many classic incremental clustering and evolutionary clustering algorithms have been proposed to detect the communities in dynamic networks. However, these algorithms rare to consider the importance of nodes, the overlap between different communities during the process of detection. In this paper, an algorithm based on core nodes was proposed which could not only detect dynamic overlapping communities, but also trace the evolution of network communities. Meanwhile, a three-way representation of a community by a pair of sets is introduced to describe the overlapping communities. Experiment results on real-world data sets demonstrate that our proposed method performs better than the well-known dynamic community detection algorithm.
机译:现实世界中的社交网络是进化的且规模庞大的。检测社区结构可以有效地表达复杂网络的结构和特征。已经提出了许多经典的增量聚类和进化聚类算法来检测动态网络中的社区。但是,这些算法很少考虑节点的重要性,即检测过程中不同社区之间的重叠。本文提出了一种基于核心节点的算法,该算法不仅可以检测动态重叠社区,而且可以跟踪网络社区的发展。同时,引入了由一对集合组成的社区的三向表示,以描述重叠的社区。在真实数据集上的实验结果表明,我们提出的方法比众所周知的动态社区检测算法具有更好的性能。

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