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Research map / Graph learning / Graph algorithms and clustering

Between Subgraph Isomorphism and Maximum Common Subgraph

AAAI 2017 · Graph learning › Graph algorithms and clustering · approach: Graph comparison and random features · 29 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
add path-based supplemental graph constraints (k = 0) (ablation)k-less subgraph isomorphism, induced · 5,725 instancespermitted assignment pair ratioHelped
add path-based constraints as k grows to 3 (ablation)k-less subgraph isomorphism, induced · 5,725 instancespermitted assignment pair ratioHurt
iteratively increase k from 0 instead of MCS algorithms (FC, clique)maximum common induced subgraph · 5,725 instancesinstances closedHelped
iteratively increase k vs clique approach on standard MCS benchmarkmaximum common induced subgraph · MCS benchmark, 4,110 instancesinstances solved over timeHelped

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