an:06253950
Zbl 1280.68194
Shervashidze, Nino; Schweitzer, Pascal; van Leeuwen, Erik Jan; Mehlhorn, Kurt; Borgwardt, Karsten M.
Weisfeiler-Lehman graph kernels
EN
J. Mach. Learn. Res. 12, 2539-2561 (2011).
00328873
2011
j
68T05 62H30 05C90
graph kernels
Summary: We propose a family of efficient kernels for large graphs with discrete node labels. Key to our method is a rapid feature extraction scheme based on the Weisfeiler-Lehman test of isomorphism on graphs. It maps the original graph to a sequence of graphs, whose node attributes capture topological and label information. A family of kernels can be defined based on this Weisfeiler-Lehman sequence of graphs, including a highly efficient kernel comparing subtree-like patterns. Its runtime scales only linearly in the number of edges of the graphs and the length of the Weisfeiler-Lehman graph sequence. In our experimental evaluation, our kernels outperform state-of-the-art graph kernels on several graph classification benchmark data sets in terms of accuracy and runtime. Our kernels open the door to large-scale applications of graph kernels in various disciplines such as computational biology and social network analysis.