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首页> 外文期刊>Journal of Computational Methods in Sciences and Engineering >A novel two-step community detection approach based on community tree and the N-players cooperative game in large-scale social networks
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A novel two-step community detection approach based on community tree and the N-players cooperative game in large-scale social networks

机译：基于社区树的新型两步社区检测方法和大型社交网络中的N-Players合作游戏

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摘要

With the rapid development of social network, community detection has caught lots of researcher's attention. How-ever, the existing methods are difficult to solve mass data in growing large-scale networks. In this paper, a two-step method is proposed to cope with large-scale networks based on the construction of community tree and the N-players cooperative game process. In the first stage, the community tree is constructed to initialize community detection by the similarity of nodes. Next, it performs greatly for N-players cooperative game to adjust and ensure the remaining nodes or spare communities. For the transmission of the stored structure of community tree, N-players cooperative game theory (NC-GT) also exhibits the excel-lent performance on runtime. We make the evaluations on three synthetic networks and four real-world networks and the main indicates are the modularity, NMI etc. The results show NC-GT has a stable and efficient performance on large-scale compared to other algorithms. Besides, the proposed community tree provides a more convenient way to research the flexible actions on nodes, which makes it more suitable for the dynamic networks.
机译：随着社会网络的快速发展，社区检测涉及大量研究员的关注。多么，现有方法难以解决大规模网络中的质量数据。在本文中，提出了一种基于社区树的建设和N-Players合作游戏过程来应对大规模网络的两步方法。在第一阶段，构建社区树以通过节点的相似性初始化社区检测。接下来，它对N-Players合作游戏进行了很大的调整和保证剩余节点或备用社区。为了传输社区树的存储结构，N-Players合作博弈论（NC-GT）也在运行时展示了Excel-Lent性能。我们对三个合成网络和四个真实网络的评估以及主要表明是模块化，NMI等。结果显示NC-GT与其他算法相比，NC-GT在大规模上具有稳定和高效的性能。此外，建议的社区树提供了一种更方便的方法来研究节点上的灵活动作，这使得它更适合动态网络。

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