Noisy Subgraph Isomorphisms on Multiplex Networks

We address the problem of finding noisy subgraph isomorphisms on large multiplex networks. Our goal is to find as many subgraph matches as possible within a noise tolerance. We propose a novel approach based on the well-known $A^{\ast}$ search algorithm. Our approach employs new heuristics to estimate the number of missing edges of subgraph matches. This method is verified on one of the synthetic multiplex networks from the Modeling Adversarial Activity program of the Defense Advanced Research Projects Agency.

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