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Pattern Mining and Machine Learning for Demographic Sequences

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Knowledge Engineering and Semantic Web (KESW 2015)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 518))

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Abstract

In this paper, we present the results of our first studies in application of pattern mining and machine learning techniques to analysis of demographic sequences in Russia based on data of 11 generations from 1930 to 1984. The main goal is not prediction and data mining methods themselves but rather extraction of interesting patterns and knowledge acquisition from substantial datasets of demographic data. We use decision trees as techniques for demographic events prediction and emergent patterns for searching significant and potentially useful sequences.

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Authors and Affiliations

  1. National Research University Higher School of Economics, Moscow, Russia

    Dmitry I. Ignatov, Ekaterina Mitrofanova, Anna Muratova & Danil Gizdatullin

Authors
  1. Dmitry I. Ignatov
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  2. Ekaterina Mitrofanova
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  3. Anna Muratova
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  4. Danil Gizdatullin
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Corresponding author

Correspondence to Dmitry I. Ignatov .

Editor information

Editors and Affiliations

  1. Complexible Inc, Washington, District of Columbia, USA

    Pavel Klinov

  2. ITMO University, St. Petersburg, Russia

    Dmitry Mouromtsev

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Ignatov, D.I., Mitrofanova, E., Muratova, A., Gizdatullin, D. (2015). Pattern Mining and Machine Learning for Demographic Sequences. In: Klinov, P., Mouromtsev, D. (eds) Knowledge Engineering and Semantic Web. KESW 2015. Communications in Computer and Information Science, vol 518. Springer, Cham. https://doi.org/10.1007/978-3-319-24543-0_17

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  • DOI: https://doi.org/10.1007/978-3-319-24543-0_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-24542-3

  • Online ISBN: 978-3-319-24543-0

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