超越平均：从复杂网络中的局部特征检测全局奇异节点
Beyond the average: detecting global singular nodes from local features in complex networks
摘要：
偏离平均值可以提供有关自然系统组织的有价值的见解。本文将这一重要原则扩展到更系统地识别和分析复杂网络中的奇异局部连通模式。四个测量量化不同的和互补的功能，每个节点周围的连接计算和多元统计方法，然后应用，以确定离群值。所提出的概念和方法的潜力示出相对于一个词的关联网络。
英文摘要：
Deviations from the average can provide valuable insights about the organization of natural systems. This article extends this important principle to the more systematic identification and analysis of singular local connectivity patterns in complex networks. Four measurements quantifying different and complementary features of the connectivity around each node are calculated and multivariate statistical methods are then applied in order to identify outliers. The potential of the presented concepts and methodology is illustrated with respect to a word association network.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
