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A simple strategy to explore a network is to use a random-walk where the walker jumps from one node to an adjacent node at random. It is known that biasing the random jump, the walker can explore every walk of the same length with equal probability, this is known as a Maximal Entropy Random Walk (MERW). To construct a MERW requires the knowledge of the largest eigenvalue and corresponding eigenvector of the adjacency matrix, this requires global knowledge of the network. When this globalarXiv:1709.07715v1 fatcat:uzx75cyv65cgbihc2ir2vaeqpy