In this paper we present a novel graph kernel framework inspired the by the Weisfeiler-Lehman (WL) isomorphism tests. Any WL test comprises a relabelling phase of the nodes based on test-specific information extracted from the graph, for example the set of neighbours of a node. We defined a novel relabelling and derived two kernels of the framework from it. The novel kernels are very fast to compute and achieve state-of-the-art results on five real-world datasets.
CITATION STYLE
Da San Martino, G., Navarin, N., & Sperduti, A. (2014). Graph kernels exploiting weisfeiler-lehman graph isomorphism test extensions. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8835, pp. 93–100). Springer Verlag. https://doi.org/10.1007/978-3-319-12640-1_12
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