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German-Japanese Interchange of Data Analysis Results pp 203–211Cite as

An Automatic Extraction of Academia-Industry Collaborative Research and Development Documents on the Web

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Abstract

This research focuses on an automatic extraction method of Japanese documents describing University-Industry (U-I) relations from the Web. The method proposed here consists of a preprocessing step for Japanese texts and a classification step with a SVM. The feature selection process is especially tuned up for U-I relations documents. A U-I document extraction experiment has been conducted and the features found to be relevant for this task are discussed.

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Notes

  1. 1.

    http://www.gnu.org/software/wget/

  2. 2.

    http://svmlight.joachims.org/

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Author information

Authors and Affiliations

  1. National Institute of Informatics, Tokyo, 101-8430, Japan

    Kei Kurakawa & Yuan Sun

  2. Japan Society for the Promotion of Science, Tokyo, 102-8472, Japan

    Nagayoshi Yamashita

  3. The Institute of Statistical Mathematics, Tokyo, 190-8562, Japan

    Yasumasa Baba

Authors
  1. Kei Kurakawa
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  2. Yuan Sun
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  3. Nagayoshi Yamashita
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  4. Yasumasa Baba
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Corresponding author

Correspondence to Kei Kurakawa .

Editor information

Editors and Affiliations

  1. Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany

    Wolfgang Gaul

  2. Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany

    Andreas Geyer-Schulz

  3. The Institute of Statistical Mathematics, Tokyo, Japan

    Yasumasa Baba

  4. Graduate School of Management and Information Systems, Tama University, Tokyo, Japan

    Akinori Okada

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© 2014 Springer International Publishing Switzerland

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Cite this paper

Kurakawa, K., Sun, Y., Yamashita, N., Baba, Y. (2014). An Automatic Extraction of Academia-Industry Collaborative Research and Development Documents on the Web. In: Gaul, W., Geyer-Schulz, A., Baba, Y., Okada, A. (eds) German-Japanese Interchange of Data Analysis Results. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Cham. https://doi.org/10.1007/978-3-319-01264-3_18

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