Graph kernels exploiting weisfeiler-lehman graph isomorphism test extensions

Giovanni Martino, Nicolò Navarin, Alessandro Sperduti

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

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.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Verlag
Pages93-100
Number of pages8
Volume8835
ISBN (Print)9783319126395
Publication statusPublished - 2014
Externally publishedYes
Event21st International Conference on Neural Information Processing, ICONIP 2014 - Kuching
Duration: 3 Nov 20146 Nov 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8835
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other21st International Conference on Neural Information Processing, ICONIP 2014
CityKuching
Period3/11/146/11/14

Fingerprint

Graph Isomorphism
kernel
Graph in graph theory
Vertex of a graph
Isomorphism
Framework

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

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). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8835). Springer Verlag.

Graph kernels exploiting weisfeiler-lehman graph isomorphism test extensions. / Martino, Giovanni; Navarin, Nicolò; Sperduti, Alessandro.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 8835 Springer Verlag, 2014. p. 93-100 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8835).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 8835, Springer Verlag, pp. 93-100, 21st International Conference on Neural Information Processing, ICONIP 2014, Kuching, 3/11/14.
Martino G, Navarin N, Sperduti A. 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. Springer Verlag. 2014. p. 93-100. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
Martino, Giovanni ; Navarin, Nicolò ; Sperduti, Alessandro. / Graph kernels exploiting weisfeiler-lehman graph isomorphism test extensions. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 8835 Springer Verlag, 2014. pp. 93-100 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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