Algorithms, Volume 12, Issue 10 (October 2019) – 22 articles
Cover Story (view full-size image): Temporal networks are graphs in which edges have temporal labels, specifying their starting and traversal times. Ignoring this information might cause wrong conclusions concerning the reachability properties of the graph. On the other hand, computing these properties exactly may turn out to be computationally unfeasible due to the huge number of temporal edges. In this paper we show how the probabilistic counting approach can be used to approximately compute the sizes of the temporal reachability cones, and how we can approximate the temporal neighborhood function (i.e., the number of pairs of nodes reachable from one another in a given time interval) of large temporal networks in a few seconds. Finally, we apply our algorithm in order to analyze and compare the behavior of 25 public transportation networks. View this paper
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