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Evolution of Characteristic Tree Structured Patterns from Semistructured Documents

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AI 2006: Advances in Artificial Intelligence (AI 2006)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4304))

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Abstract

Due to the rapid growth of Internet usage, semistructured documents such as XML/HTML files have been rapidly increasing. Genetic Programming is widely used as a method for evolving solutions from structured data and is shown to be useful for evolving highly structured knowledge. We apply genetic programming to the evolution of characteristic tree structured patterns from semistructured documents.

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References

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Author information

Authors and Affiliations

  1. Faculty of Information Sciences, Hiroshima City University, Hiroshima, 731-3194, Japan

    Katsushi Inata, Tetsuhiro Miyahara, Hiroaki Ueda & Kenichi Takahashi

Authors
  1. Katsushi Inata
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  2. Tetsuhiro Miyahara
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  3. Hiroaki Ueda
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  4. Kenichi Takahashi
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Editor information

Editors and Affiliations

  1. DisPRR, National ICT Australia Ltd, QLD, Australia

    Abdul Sattar

  2. School of Computing, University of Tasmania, Sandy Bay, 7005, Tasmania, Australia

    Byeong-ho Kang

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© 2006 Springer-Verlag Berlin Heidelberg

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Inata, K., Miyahara, T., Ueda, H., Takahashi, K. (2006). Evolution of Characteristic Tree Structured Patterns from Semistructured Documents. In: Sattar, A., Kang, Bh. (eds) AI 2006: Advances in Artificial Intelligence. AI 2006. Lecture Notes in Computer Science(), vol 4304. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11941439_148

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  • DOI: https://doi.org/10.1007/11941439_148

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-49787-5

  • Online ISBN: 978-3-540-49788-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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