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An efficient agent-based algorithm for overlapping community detection using nodes' closeness

机译:一种基于代理的高效基于节点接近度的社区重叠检测算法

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摘要

Communities are groups of nodes forming tightly connected units in networks. Some nodes can be shared between different communities of a network. The presence of overlapping nodes and their associated membership diversity is a common characteristic of social networks. Analyzing these overlapping structures can reveal valuable information about the intrinsic features of realistic complex networks, especially social networks. In this paper, we propose a novel algorithm that is able to detect overlapping and non-overlapping community structures in complex networks. This algorithm uses a number of agents for investigation of the input network. These agents consider different nodes' closeness in their investigations. Various experiments are carried out on both synthetic and real-world networks that prove that the proposed algorithm outperforms most state-of-the-art algorithms of this field both in terms of the accuracy and execution time.
机译:社区是在网络中形成紧密连接的单元的节点组。某些节点可以在网络的不同社区之间共享。重叠节点的存在及其关联的成员多样性是社交网络的共同特征。分析这些重叠的结构可以揭示有关现实的复杂网络(尤其是社交网络)的内在特征的有价值的信息。在本文中,我们提出了一种新颖的算法,能够检测复杂网络中重叠和不重叠的社区结构。该算法使用许多代理来调查输入网络。这些代理在调查中考虑不同节点的亲密性。在合成网络和实际网络上都进行了各种实验,证明在算法的准确性和执行时间方面,所提出的算法优于该领域的大多数最新算法。

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