Detecting network communities:: a new systematic and efficient algorithm -: art. no. P10012
Detecting network communities:: a new systematic and efficient algorithm -: art. no. P10012
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DOI：
10.1088/1742-5468/2004/10/p10012
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发表时间：
2004-10-01
影响因子：
2.4
通讯作者：
Mu単oz, MA
中科院分区：
文献类型：
--
作者：
Donetti, L;Mu単oz, MA
提出了一种快速有效的复杂网络社区发现算法。该方法利用谱特性的图形拉普拉斯矩阵结合层次聚类技术，并包括一个程序，用于最大限度地提高输出的“模块化”。它的性能与其他现有的方法相比，适用于不同的知名实例的复杂网络的社区结构，计算机生成的和从真实的世界。我们的结果是，在所有的情况下测试，至少一样好，用任何其他方法获得的最好的，并在大多数情况下比方法提供类似的质量结果更快。这将该算法转换为一个有价值的计算工具，用于检测和分析复杂网络中的社区和模块化结构。
An efficient and relatively fast algorithm for the detection of communities in complex networks is introduced. The method exploits spectral properties of the graph Laplacian matrix combined with hierarchical clustering techniques, and includes a procedure for maximizing the 'modularity' of the output. Its performance is compared with that of other existing methods, as applied to different well-known instances of complex networks with a community structure, both computer generated and from the real world. Our results are, in all the cases tested, at least as good as the best ones obtained with any other methods, and faster in most of the cases than methods providing similar quality results. This converts the algorithm into a valuable computational tool for detecting and analysing communities and modular structures in complex networks.