基于复杂网络社团结构理论，提出了一种同调等值的新算法。
Based on the community structure theory of complex network, a new coherency-based dynamic equivalence algorithm is proposed.
目前人们已经提出了很多算法用于寻找复杂网络中存在的社团结构。
Finding community structure is a very popular issue in researches of complex networks.
基于改进的SNN相似度矩阵与谱平分法，提出了一种寻找复杂网络社团结构的算法。
Based on the improved SNN similarity matrix and spectral bisection method, this paper proposed a new algorithm for detecting the community structure in complex networks.
最后将复杂网络中的社团结构引入投入产出关联网络中，分析和研究国民经济产业结构。
Finally, the community structure concept in complex network is introduced into the input-output relevancy network to investigate and analyze the national economic industry structure.
近年来，以交互作用图建模并通过各种图聚类技术发现复杂网络内部隐含的社团结构已成为研究热点。
In recent years, it is becoming popular that modeling by interaction networks and finding the internal social structure from the complex networks by graph clustering method.
社团结构是反映网络结构整体性质的重要特征，网络的稳定性和健壮性在很大程度上取决于网络的社团结构特征。
Community structure not only reflects the important characteristics of overall structure properties of networks, but also it determines the stability and the robustness to a large extent.
社团结构是反映网络结构整体性质的重要特征，网络的稳定性和健壮性在很大程度上取决于网络的社团结构特征。
Community structure not only reflects the important characteristics of overall structure properties of networks, but also it determines the stability and the robustness to a large extent.
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