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Detecting overlapping community structure of complex networks in nature and society

机译:检测自然和社会中复杂网络的重叠社区结构

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As the research of the complex network is becoming more and more hot in recent years, a lot of different characteristics have been found in the research of complex network, such as small-world property and scale-free properties. Community structure is one of the most relevant features of complex networks as well. Community, in which vertices are joined tightly together, between which there are only looser edges, exists in many real networks. Community detection is an important methodology for understanding the function and the organization of real-world networks. In this article, we arm to put forward a useful method to improve the efficiency and the validity of overlapping community detection. Such a measure can accurately detect community in both known network and standard synthetic network. Finally we apply our method to the real-world network whose community structure is known, and find that the results show high accuracy and efficiency.
机译:近年来,随着对复杂网络的研究越来越热,在复杂网络的研究中发现了许多不同的特征,例如小世界性质和无标度性质。社区结构也是复杂网络最相关的特征之一。在许多实际的网络中都存在社区,在这些社区中,顶点紧密地连接在一起,而顶点之间只有较宽松的边缘。社区检测是了解现实世界网络的功能和组织的一种重要方法。在本文中,我们将提出一种有用的方法来提高重叠社区检测的效率和有效性。这样的措施可以准确地检测已知网络和标准合成网络中的社区。最后,我们将我们的方法应用于已知社区结构的现实世界网络中,发现结果显示出较高的准确性和效率。

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