Fast Algorithm for Graph Isomorphism Testing

EXPERIMENTAL ALGORITHMS, PROCEEDINGS(2009)

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摘要
In this paper we present a novel approach to the graph isomorphism problem. We combine a direct approach, that tries to find a mapping between the two input graphs using backtracking, with a (possibly partial) automorphism precomputing that allows to prune the search tree. We propose an algorithm, conauto , that has a space complexity of O (n 2 logn ) bits. It runs in time O (n 5) with high probability if either one of the input graphs is a G (n ,p ) random graph, for p *** [*** (ln 4 n / n ln ln n ), 1 *** *** (ln 4 n / n ln ln n )]. We compare the practical performance of conauto with other popular algorithms, with an extensive collection of problem instances. Our algorithm behaves consistently for directed, undirected, positive, and negative cases. Additionally, when it is slower than any of the other algorithms, it is only by a small factor.
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关键词
random graph,extensive collection,novel approach,automorphism precomputing,graph isomorphism testing,problem instance,time o,graph isomorphism problem,fast algorithm,popular algorithm,direct approach,input graph,data mining,pattern recognition,information retrieval,computer vision,vlsi,graph isomorphism
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