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A fast and efficient heuristic algorithm for detecting community structures in complex networks

机译:一种快速高效的启发式算法,用于检测复杂网络中的社区结构

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摘要

Community structure is an important property of complex networks. How to detect the communities is significant for understanding the network structure and to analyze the network properties. Many algorithms. such as K-L and GN, have been proposed to detect community structures in complex networks. According to daily experience, a community should have many nodes and connections. Based oil these principles and existing researches, a fast and efficient algorithm for detecting community structures in complex networks is proposed in this paper. The key strategy of the algorithm is to mine a node with the closest relations with the community and assign it to this community. Four real-world networks are used to test the performance of the algorithm. Experimental results demonstrate that the algorithm proposed is rather efficient for detecting community structures in complex networks.
机译:社区结构是复杂网络的重要属性。如何检测社区对于了解网络结构和分析网络属性很重要。许多算法。已经提出了诸如K-L和GN之类的方法来检测复杂网络中的社区结构。根据日常经验,社区应具有许多节点和连接。基于这些原理和已有研究,提出了一种快速有效的复杂网络社区结构检测算法。该算法的关键策略是挖掘与社区关系最密切的节点,并将其分配给该社区。四个真实世界的网络用于测试算法的性能。实验结果表明,所提出的算法对于检测复杂网络中的社区结构非常有效。

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