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JSAI International Symposium on Artificial Intelligence

JSAI-isAI 2013: New Frontiers in Artificial Intelligence pp 337–351Cite as

A Comprehensive Study of Tree Kernels

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8417))

Abstract

Tree kernels are an effective method to capture the structural information of tree data of various applications and many algorithms have been proposed. Nevertheless, we do not have sufficient knowledge about how to select good kernels. To answer this question, we focus on 32 tree kernel algorithms defined within a certain framework to engineer positive definite kernels, and investigate them under two different parameter settings. The result is amazing. Three of the 64 tree kernels outperform the others, and their superiority proves statistically significant through t-tests. These kernels include the benchmark tree kernels proposed in the literature, while many of them are introduced and tested for the first time in this paper.

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Author information

Authors and Affiliations

  1. Graduate School of Applied Informatics, University of Hyogo, 7-1-28 Minatojima-minamimachi, Chuo-ku, Kobe, Hyogo, 650-0047, Japan

    Kilho Shin

  2. Computer Centre, Gakushuin University, 1-5-1 Mejiro, Toshima, Tokyo, 171-8588, Japan

    Tetsuji Kuboyama

Authors
  1. Kilho Shin
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  2. Tetsuji Kuboyama
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Corresponding author

Correspondence to Tetsuji Kuboyama .

Editor information

Editors and Affiliations

  1. Seikei University, Musashino-shi, Tokyo, Japan

    Yukiko Nakano

  2. National Institute of Informatics Research Division, Tokyo, Japan

    Ken Satoh

  3. Ochanomizu University, Tokyo, Japan

    Daisuke Bekki

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© 2014 Springer International Publishing Switzerland

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Shin, K., Kuboyama, T. (2014). A Comprehensive Study of Tree Kernels. In: Nakano, Y., Satoh, K., Bekki, D. (eds) New Frontiers in Artificial Intelligence. JSAI-isAI 2013. Lecture Notes in Computer Science(), vol 8417. Springer, Cham. https://doi.org/10.1007/978-3-319-10061-6_22

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  • DOI: https://doi.org/10.1007/978-3-319-10061-6_22

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-10060-9

  • Online ISBN: 978-3-319-10061-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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