Abstract: Co-Simrank is a useful Simrank-like measure of similarity based on graph structure. The existing method iteratively computes each pair of Co-Simrank score from a dot product of two Pagerank vectors, entailing O(log(1/e)*n^3) time to compute all pairs of Co-Simranks in a graph with n nodes, to attain a desired accuracy e. In this study, we devise a model, Co-Simmate, to speed up the retrieval of all pairs of Co-Simranks to O(log2 (log(1/e))*n^3) time. Moreover, we show the optimality of Co-Simmate among other hop-(u^k) variations, and integrate it with a matrix decomposition based method on singular graphs to attain higher efficiency. The viable experiments verify the superiority of Co-Simmate to others.
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