Clique and constraint models for maximum common (Connected) subgraph problems

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Abstract

The maximum common subgraph problem is to find the largest subgraph common to two given graphs. This problem can be solved either by constraint-based search, or by reduction to the maximum clique problem. We evaluate these two models using modern algorithms, and see that the best choice depends mainly upon whether the graphs have labelled edges. We also study a variant of this problem where the subgraph is required to be connected. We introduce a filtering algorithm for this property and show that it may be combined with a restricted branching technique for the constraint-based approach. We show how to implement a similar branching technique in clique-inspired algorithms. Finally, we experimentally compare approaches for the connected version, and see again that the best choice depends on whether graphs have labels.

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McCreesh, C., Ndiaye, S. N., Prosser, P., & Solnon, C. (2016). Clique and constraint models for maximum common (Connected) subgraph problems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9892 LNCS, pp. 350–368). Springer Verlag. https://doi.org/10.1007/978-3-319-44953-1_23

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