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Mining Frequent Trees with Node-Inclusion Constraints

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Advances in Knowledge Discovery and Data Mining (PAKDD 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3518))

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Abstract

In this paper, we propose an efficient algorithm enumerating all frequent subtrees containing all special nodes that are guaranteed to be included in all trees belonging to a given data. Our algorithm is a modification of TreeMiner algorithm [10] so as to efficiently generate only candidate subtrees satisfying our constraints. We report mining results obtained by applying our algorithm to the problem of finding frequent structures containing the name and reputation of given restaurants in Web pages collected by a search engine.

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Author information

Authors and Affiliations

  1. Graduate School of Information Science and Technology, Hokkaido University, Kita 14, Nishi 9, Kita-ku, Sapporo, 060-0814, Japan

    Atsuyoshi Nakamura & Mineichi Kudo

Authors
  1. Atsuyoshi Nakamura
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  2. Mineichi Kudo
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Editor information

Editors and Affiliations

  1. Japan Advanced Institute of Science and Technology, Asahidai 1-1, 923-12292, Nomi, Japan

    Tu Bao Ho

  2. University of Hong Kong, Pokfulam Road, Hong Kong, China

    David Cheung

  3. Department of Computer Science and Engineering, Arizona State University, Tempe, Arizona, USA

    Huan Liu

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© 2005 Springer-Verlag Berlin Heidelberg

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Nakamura, A., Kudo, M. (2005). Mining Frequent Trees with Node-Inclusion Constraints. In: Ho, T.B., Cheung, D., Liu, H. (eds) Advances in Knowledge Discovery and Data Mining. PAKDD 2005. Lecture Notes in Computer Science(), vol 3518. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11430919_101

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  • DOI: https://doi.org/10.1007/11430919_101

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-26076-9

  • Online ISBN: 978-3-540-31935-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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