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Multi-perspective Analysis of Mobile Phone Call Data Records: A Visual Analytics Approach

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Book cover Business Intelligence (eBISS 2014)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 205))

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Abstract

Analysis of human mobility is currently a hot research topic in data mining, geographic information science and visual analytics. While a wide variety of methods and tools are available, it is still hard to find recommendations for considering a data set systematically from multiple perspectives. To fill this gap, we demonstrate a workflow of a comprehensive analysis of a publicly available data set about mobile phone calls of a large population over a long time period. We pay special attention to the evaluation of data properties. We outline potential applications of the proposed methods.

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Notes

  1. 1.

    Public holidays in Ivory Coast in 2012: http://www.asaralo.com/index.php?option=com_content&view=article&id=2367:public-holidays-in-cote-divoire&catid=160:african-public-holiday&Itemid=2598.

  2. 2.

    http://en.wikipedia.org/wiki/Ivory_Coast#Religion.

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Author information

Authors and Affiliations

  1. Fraunhofer Institute IAIS, Schloss Birlinghoven, 53757, Sankt Augustin, Germany

    Gennady Andrienko, Natalia Andrienko & Georg Fuchs

  2. City University London, Northampton Square, London, EC1V 0HB, UK

    Gennady Andrienko & Natalia Andrienko

Authors
  1. Gennady Andrienko
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  2. Natalia Andrienko
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  3. Georg Fuchs
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Corresponding author

Correspondence to Gennady Andrienko .

Editor information

Editors and Affiliations

  1. Université Libre de Bruxelles, Brussels, Belgium

    Esteban Zimányi

  2. Technische Universtät Berlin, Berlin, Germany

    Ralf-Detlef Kutsche

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Andrienko, G., Andrienko, N., Fuchs, G. (2015). Multi-perspective Analysis of Mobile Phone Call Data Records: A Visual Analytics Approach. In: Zimányi, E., Kutsche, RD. (eds) Business Intelligence. eBISS 2014. Lecture Notes in Business Information Processing, vol 205. Springer, Cham. https://doi.org/10.1007/978-3-319-17551-5_2

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  • DOI: https://doi.org/10.1007/978-3-319-17551-5_2

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-17550-8

  • Online ISBN: 978-3-319-17551-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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