论文标题
识别高阶网络中显着相互作用节点的最大集合
Identifying maximal sets of significantly interacting nodes in higher-order networks
论文作者
论文摘要
我们介绍了一种检测高阶网络中经统计验证的简单的方法。经统计验证的简单表示任何大小的最大节点集集，这些节点始终如一地集体交互，并且不包括仅出现偶尔出现的共同交互节点。使用经过适当设计的高阶基准测试，我们表明我们的方法在最大组合可能会被稀释为包括偶尔参与者的较大尺寸的相互作用的系统中非常有效。通过将我们的方法应用于两个现实世界数据集，我们还展示了它如何允许检测其节点具有重要相似之处的简形，从而提供了有关现实世界高阶网络生成过程的新见解。
We introduce a method for the detection of Statistically Validated Simplices in higher-order networks. Statistically validated simplices represent the maximal sets of nodes of any size that consistently interact collectively and do not include co-interacting nodes that appears only occasionally. Using properly designed higher-order benchmarks, we show that our approach is highly effective in systems where the maximal sets are likely to be diluted into interactions of larger sizes that include occasional participants. By applying our method to two real world datasets, we also show how it allows to detect simplices whose nodes are characterized by significant levels of similarity, providing new insights on the generative processes of real world higher-order networks.
