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Multiview graph kernel based on popular methods
Author(s): Kai Liu; Yi Zhang; Kai Lu; Xiaoping Wang; Xin Wang
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Paper Abstract

Graph classification is a challenging problem that assigns the structured data into several categories. The success of kernel methods in graph classification has aroused many designs of novel graph kernel. In this paper, we present a multiview graph kernel, a new method to combine the advantages of multiple kernel functions (Graphlet kernel and Weisfeiler-Lehman kernel). Experiments on several benchmark datasets show that multiview graph kernel could achieve significant improvements compared with the original graph kernels.

Paper Details

Date Published: 3 January 2020
PDF: 7 pages
Proc. SPIE 11373, Eleventh International Conference on Graphics and Image Processing (ICGIP 2019), 1137320 (3 January 2020); doi: 10.1117/12.2557752
Show Author Affiliations
Kai Liu, National Univ. of Defense Technology (China)
Yi Zhang, National Univ. of Defense Technology (China)
Kai Lu, National Univ. of Defense Technology (China)
Xiaoping Wang, Hunan Univ. (China)
Xin Wang, National Univ. of Defense Technology (China)


Published in SPIE Proceedings Vol. 11373:
Eleventh International Conference on Graphics and Image Processing (ICGIP 2019)
Zhigeng Pan; Xun Wang, Editor(s)

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