Foundations and Advances in Data Mining

Chu, Wesley W.; Lin, Tsau Young

doi:10.1007/b104039

Cited by 10 publications

(1 citation statement)

References 91 publications

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“…Here, we denote by p i and w i the probability that node i is found within the set of SNs of, respectively, a multiplex network (ground truth) and a specific single-layer representation of that multiplex. To compare the sets represented by w i to the ground truth sets, we adopt three standard metrics in information retrieval [45,46], namely precision, recall and the Van Rijsbergen's F 1 score: Precision is defined as…”

Section: Accuracy and Sensitivitymentioning

confidence: 99%

Optimal percolation on multiplex networks

2017

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Optimal percolation is the problem of finding the minimal set of nodes whose removal from a network fragments the system into non-extensive disconnected clusters. The solution to this problem is important for strategies of immunization in disease spreading, and influence maximization in opinion dynamics. Optimal percolation has received considerable attention in the context of isolated networks. However, its generalization to multiplex networks has not yet been considered. Here we show that approximating the solution of the optimal percolation problem on a multiplex network with solutions valid for single-layer networks extracted from the multiplex may have serious consequences in the characterization of the true robustness of the system. We reach this conclusion by extending many of the methods for finding approximate solutions of the optimal percolation problem from single-layer to multiplex networks, and performing a systematic analysis on synthetic and real-world multiplex networks.

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Section: Accuracy and Sensitivitymentioning

confidence: 99%