首页> 外文期刊>Computers & mathematics with applications >A vector partitioning approach to detecting community structure in complex networks
【24h】

A vector partitioning approach to detecting community structure in complex networks

机译:在复杂网络中检测社区结构的矢量划分方法

获取原文
获取原文并翻译 | 示例
           

摘要

In recent years, the problem of community structure detection has attracted more and more attention and many approaches have been proposed. Recently, Newman pointed out that this issue can be transformed into the problem of constrained maximization of the assignment matrix over possible divisions of a network. He presents further that this maximization process can be written in terms of the eigenspectrum of the "modularity matrix". On the basis of this work and the vector partition approach in computer science, we propose a kind of multiway division approach for detecting community structure of complex networks. Experimental results indicate that the algorithm works well and is effective at finding both good communities and the appropriate number of communities.
机译:近年来,社区结构检测问题引起了越来越多的关注,并提出了许多方法。最近,纽曼指出,这个问题可以转化为在网络的可能划分上分配矩阵的约束最大化的问题。他进一步提出,可以根据“模量矩阵”的本征谱来编写此最大化过程。在此工作和计算机科学中的矢量划分方法的基础上,我们提出了一种用于检测复杂网络社区结构的多路划分方法。实验结果表明,该算法运行良好,并且在找到良好的社区和适当数量的社区方面均有效。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号