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Authors: Tetsuya Kataoka and Akihiro Inokuchi

Affiliation: Kwansei Gakuin University, Japan

ISBN: 978-989-758-173-1

Keyword(s): Graph Classification, Support Vector Machine, Graph Kernel, Hadamard Code.

Related Ontology Subjects/Areas/Topics: Classification ; Kernel Methods ; Pattern Recognition ; Theory and Methods

Abstract: Kernel methods such as Support Vector Machines (SVMs) are becoming increasingly popular because of their high performance on graph classification problems. In this paper, we propose two novel graph kernels called the Hadamard Code Kernel (HCK) and the Shortened HCK (SHCK). These kernels are based on the Hadamard code, which is used in spread spectrum-based communication technologies to spread message signals. The proposed graph kernels are equivalent to the Neighborhood Hash Kernel (NHK), one of the fastest graph kernels, and comparable to the Weisfeiler-Lehman Subtree Kernel (WLSK), one of the most accurate graph kernels. The fundamental performance and practicality of the proposed graph kernels are evaluated using three real-world datasets.

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Paper citation in several formats:
Kataoka, T. and Inokuchi, A. (2016). Hadamard Code Graph Kernels for Classifying Graphs.In Proceedings of the 5th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-173-1, pages 24-32. DOI: 10.5220/0005634700240032

@conference{icpram16,
author={Tetsuya Kataoka. and Akihiro Inokuchi.},
title={Hadamard Code Graph Kernels for Classifying Graphs},
booktitle={Proceedings of the 5th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2016},
pages={24-32},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005634700240032},
isbn={978-989-758-173-1},
}

TY - CONF

JO - Proceedings of the 5th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - Hadamard Code Graph Kernels for Classifying Graphs
SN - 978-989-758-173-1
AU - Kataoka, T.
AU - Inokuchi, A.
PY - 2016
SP - 24
EP - 32
DO - 10.5220/0005634700240032

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