...
首页> 外文期刊>International journal of machine learning and cybernetics >An augmented Lagrangian alternating direction method for overlapping community detection based on symmetric nonnegative matrix factorization
【24h】

An augmented Lagrangian alternating direction method for overlapping community detection based on symmetric nonnegative matrix factorization

机译:基于对称非负矩阵分解的增强拉格朗日交替方向重叠社区检测

获取原文
获取原文并翻译 | 示例
           

摘要

In this paper, we present an augmented Lagrangian alternating direction algorithm for symmetric nonnegative matrix factorization. The convergence of the algorithm is also proved in detail and strictly. Then we present a modified overlapping community detection method which is based on the presented symmetric nonnegative matrix factorization algorithm. We apply the modified community detection method to several real world networks. The obtained results show the capability of our method in detecting overlapping communities, hubs and outliers. We find that our experimental results have better quality than several competing methods for identifying communities.
机译:在本文中,我们提出了一种用于对称非负矩阵分解的增强拉格朗日交替方向算法。还详细,严格地证明了算法的收敛性。然后,我们提出了一种基于提出的对称非负矩阵分解算法的改进的重叠社区检测方法。我们将改进的社区检测方法应用于多个现实世界网络。获得的结果表明我们的方法能够检测重叠的社区,中心和离群值。我们发现我们的实验结果比鉴定社区的几种竞争方法具有更好的质量。

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