你不应该通过：多维复杂网络中基于最短路径中心性的伪路径避免
You Shall not Pass: Avoiding Spurious Paths in Shortest-Path Based Centralities in Multidimensional Complex Networks
摘要：
在复杂网络分析中，基于最短路径的中心性，如介数和贴近度，被广泛使用。最近，许多复杂系统被表示为时变、多层和时变多层网络，即多维（或高阶）网络。然而，众所周知，聚合过程可能会在这种多维（高阶）网络的聚合视图上创建虚假路径。因此，这些虚假路径可能导致基于最短路径的中心性度量产生不正确的结果，从而破坏网络中心性分析。在这种情况下，我们提出了一种方法，能够避免考虑虚假路径时，计算中心的最短路径在多维（或高阶）网络。我们的方法是基于多方面图~（MAG）来表示多维网络，我们表明，著名的中心算法可以直接适应MAG环境。此外，我们表明，通过使用这种MAG表示，陷阱通常与虚假路径在多维网络中的聚合所产生的聚合过程中，可以避免的时候。因此，基于最短路径的中心性被确保为多维网络正确计算，而不考虑可能导致不正确结果的虚假路径。我们还提出了一个案例研究，显示了虚假路径的影响，在计算最短路径，因此最短路径为基础的中心，如介数和接近度，从而说明了这一贡献的重要性。
英文摘要：
In complex network analysis, centralities based on shortest paths, such as betweenness and closeness, are widely used. More recently, many complex systems are being represented by time-varying, multilayer, and time-varying multilayer networks, i.e. multidimensional (or high order) networks. Nevertheless, it is well-known that the aggregation process may create spurious paths on the aggregated view of such multidimensional (high order) networks. Consequently, these spurious paths may then cause shortest-path based centrality metrics to produce incorrect results, thus undermining the network centrality analysis. In this context, we propose a method able to avoid taking into account spurious paths when computing centralities based on shortest paths in multidimensional (or high order) networks. Our method is based on MultiAspect Graphs~(MAG) to represent the multidimensional networks and we show that well-known centrality algorithms can be straightforwardly adapted to the MAG environment. Moreover, we show that, by using this MAG representation, pitfalls usually associated with spurious paths resulting from aggregation in multidimensional networks can be avoided at the time of the aggregation process. As a result, shortest-path based centralities are assured to be computed correctly for multidimensional networks, without taking into account spurious paths that could otherwise lead to incorrect results. We also present a case study that shows the impact of spurious paths in the computing of shortest paths and consequently of shortest-path based centralities, such as betweenness and closeness, thus illustrating the importance of this contribution.
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。
