Nowadays it is not uncommon to have to deal with dissemination on multi-layered networks and often finding the source of said propagation can be a crucial task. In this paper we tackle this exact problem with a maximum likelihood approach that we extend to be operational on multi-layered graphs. We test our method for source location estimation on synthetic networks and outline its potential strengths and limitations. We also observe some non-trivial and perhaps surprising phenomena where the more of the system one observes the worse the results become whereas increased problem complexity in the form of more layers can actually improve our performance.
翻译:如今,处理多层次网络的传播问题并经常发现上述传播的来源是一项关键任务,这并非罕见。在本文件中,我们用一种我们推广到多层次图上运作的最可能的方法来解决这个确切的问题。我们测试了我们对于合成网络的源位置估计方法,并概述了其潜在的长处和局限性。我们还观察到一些非三角现象,或许是令人惊讶的现象,在这种现象中,人们越是看到结果越是糟糕,而以多层形式出现的问题更加复杂性实际上可以改善我们的业绩。