We propose graph kernels based on subgraph matchings, i.e. structure-preserving bijections between subgraphs. While recently proposed kernels based on common subgraphs (Wale et al., 2008; Shervashidze et al., 2009) in general can not be applied to attributed graphs, our approach allows to rate mappings of subgraphs by a flexible scoring scheme comparing vertex and edge attributes by kernels. We show that subgraph matching kernels generalize several known kernels. To compute the kernel we propose a graphtheoretical algorithm inspired by a classical relation between common subgraphs of two graphs and cliques in their product graph observed by Levi (1973) . Encouraging experimental results on a classification task of realworld graphs are presented.
The subgraph matching kernel REF identifies common subgraphs based on cliques in the product graph of two graphs.
Subgraph Matching Kernels for Attributed Graphs
ICML
Computer Science Mathematics