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Similarity Analysis of Survey on Employment Trends in Japan

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Intelligent and Evolutionary Systems

Part of the book series: Proceedings in Adaptation, Learning and Optimization ((PALO,volume 8))

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Abstract

This paper analyzes the characteristics of employment in Japan from open data. Applying methods of AI research field to Survey on Employment Trends in Japan as the way to understand a trend of economic activity is proposed.

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Reference

  1. Carvalho, V.M.: From micro to macro via production networks. Journal of Economic Perspectives 28(4), 23–48 (2014)

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Authors and Affiliations

  1. National Defense Academy of Japan, Fukuoka Institute of Technology, Fukuoka, Japan

    Masao Kubo, Hiroshi Sato, Akihiro Yamaguchi & Yuji Aruka

  2. Chuo University, Tokyo, Japan

    Masao Kubo, Hiroshi Sato, Akihiro Yamaguchi & Yuji Aruka

Authors
  1. Masao Kubo
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  2. Hiroshi Sato
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  3. Akihiro Yamaguchi
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  4. Yuji Aruka
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Corresponding author

Correspondence to Masao Kubo .

Editor information

Editors and Affiliations

  1. School of Engineering and Information Technology, Australian Defence Force Academy, The University of New South Wales, Canberra, Australian Capital Territory, Australia

    George Leu

  2. School of Engineering and Information Technology, Australian Defence Force Academy, The University of New South Wales, Canberra, Australian Capital Territory, Australia

    Hemant Kumar Singh

  3. School of Engineering and Information Technology, Australian Defence Force Academy, The University of New South Wales, Canberra, Australian Capital Territory, Australia

    Saber Elsayed

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© 2017 Springer International Publishing AG

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Kubo, M., Sato, H., Yamaguchi, A., Aruka, Y. (2017). Similarity Analysis of Survey on Employment Trends in Japan. In: Leu, G., Singh, H., Elsayed, S. (eds) Intelligent and Evolutionary Systems. Proceedings in Adaptation, Learning and Optimization, vol 8. Springer, Cham. https://doi.org/10.1007/978-3-319-49049-6_15

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  • DOI: https://doi.org/10.1007/978-3-319-49049-6_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-49048-9

  • Online ISBN: 978-3-319-49049-6

  • eBook Packages: EngineeringEngineering (R0)

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