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Empirical Study on Usefulness of Algorithm SACwRApper for Reputation Extraction from the WWW

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Knowledge-Based Intelligent Information and Engineering Systems (KES 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3684))

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Abstract

We consider the problem of extracting texts related to a given keyword from Web pages collected by a search engine. Recently, we proposed a method using both structural and content information [1,2]. In our previous paper, we reported good extraction performance of our method only for Ramen-shop dataset written in Japanese. In this paper, we examine it for datasets of other kind of restaurants, and also for a dataset written in English. We discuss some modification for performance improvement.

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References

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Author information

Authors and Affiliations

  1. Division of Computer Science, Graduate School of Information Science and Technology, Hokkaido University, Sapporo, Hokkaido, 060-0814, Japan

    Hiroyuki Hasegawa, Mineichi Kudo & Atsuyoshi Nakamura

Authors
  1. Hiroyuki Hasegawa
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  2. Mineichi Kudo
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  3. Atsuyoshi Nakamura
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Editor information

Editors and Affiliations

  1. School of Business, La Trobe University, 3086, Melbourne, Victoria, Australia

    Rajiv Khosla

  2. Centre for SMART systems Engineering Research Centre, University of Brighton, Moulsecoomb, BN2 4GJ, Brighton, UK

    Robert J. Howlett

  3. School of Electrical and Information Engineering, Knowledge Based Intelligent Engineering Systems Centre, University of South Australia, 5095, Mawson Lakes, SA, Australia

    Lakhmi C. Jain

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© 2005 Springer-Verlag Berlin Heidelberg

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Hasegawa, H., Kudo, M., Nakamura, A. (2005). Empirical Study on Usefulness of Algorithm SACwRApper for Reputation Extraction from the WWW. In: Khosla, R., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2005. Lecture Notes in Computer Science(), vol 3684. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11554028_93

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  • DOI: https://doi.org/10.1007/11554028_93

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28897-8

  • Online ISBN: 978-3-540-31997-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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