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Graph Invariant Kernels
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- Orsini, F (author)
- Department of Computer Science, Katholieke Universiteit Leuven, Heverlee, Belgium; Department of Information Engineering, Università degli Studi di Firenze, Firenze, Italy
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- Frasconi, P (author)
- Department of Information Engineering, Università degli Studi di Firenze, Firenze, Italy
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- De Raedt, Luc, 1964- (author)
- Department of Computer Science, Katholieke Universiteit Leuven, Heverlee, Belgium
- (creator_code:org_t)
- Palo Alto : AAAI Press, 2015
- 2015
- English.
- In: Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence. - Palo Alto : AAAI Press. - 9781577357384 ; , s. 3756-3762
- Conference paper (peer-reviewed)
Abstract
Subject headings
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- We introduce a novel kernel that upgrades the Weisfeiler-Lehman and other graph kernels to effectively exploit high-dimensional and continuous vertex attributes. Graphs are first decomposed into subgraphs. Vertices of the subgraphs are then compared by a kernel that combines the similarity of their labels and the similarity of their structural role, using a suitable vertex invariant. By changing this invariant we obtain a family of graph kernels which includes generalizations of Weisfeiler-Lehman, NSPDK, and propagation kernels. We demonstrate empirically that these kernels obtain state-of-the-art results on relational data sets.
Subject headings
- NATURVETENSKAP -- Data- och informationsvetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences (hsv//eng)
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- kon (subject category)
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