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Algorithms for String Pattern Discovery

  • Conference paper
Modeling Decisions for Artificial Intelligence (MDAI 2007)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4617))

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Abstract

Pattern discovery from string data is an important problem with many applications. In this paper, we give a brief overview of our work on the optimal correlated pattern discovery problem, which integrates numerical attribute information into the string pattern discovery process.

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Author information

Authors and Affiliations

  1. Department of Informatics, Kyushu University, 774 Moto-oka, Nishiku, Fukuoka 819–0395, Japan

    Hideo Bannai

Authors
  1. Hideo Bannai
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Editor information

Vicenç Torra Yasuo Narukawa Yuji Yoshida

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© 2007 Springer-Verlag Berlin Heidelberg

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Bannai, H. (2007). Algorithms for String Pattern Discovery. In: Torra, V., Narukawa, Y., Yoshida, Y. (eds) Modeling Decisions for Artificial Intelligence. MDAI 2007. Lecture Notes in Computer Science(), vol 4617. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73729-2_3

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  • DOI: https://doi.org/10.1007/978-3-540-73729-2_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-73728-5

  • Online ISBN: 978-3-540-73729-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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