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Hybrid Method of Multiple Factor Data Clusterization

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Digital Transformation and Global Society (DTGS 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1242))

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Abstract

The urgent scientific problem of multifactor clustering using various methods of normalization and averaging is investigated. Metric calculation values to improve the quality of clustering. A literary review of scientific publications on the topic of clustering social graphs and identifying communities has been carried out. The shortcomings of modern research in the field of analysis of social networks are identified. The list of network analysis metrics recommended as basic for data pre-processing is presented. The algorithm of the hybrid method of multifactorial clustering is presented, which allows reducing the computational costs of data clustering. An algorithm execution procedure is described for selecting several centrality metrics. Various methods of averaging centrality metrics are presented. This approach can significantly increase the assessment of the quality of clustering. The developed hybrid method based on averaging and the Louvain multi-factor clustering algorithm allows us to reduce computational resources. The clusterization application problem in the online community ITMO.EXPERT of the VKontakte social network is considered.

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Author information

Authors and Affiliations

  1. ITMO University, 49 Kronverksky Pr., St. Petersburg, 197101, Russia

    Andrey Televnoy, Sergei Evgenievich Ivanov & Nataliya Gorlushkina

Authors
  1. Andrey Televnoy
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  2. Sergei Evgenievich Ivanov
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  3. Nataliya Gorlushkina
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Corresponding author

Correspondence to Andrey Televnoy .

Editor information

Editors and Affiliations

  1. National Research University Higher School of Economics, St. Petersburg, Russia

    Daniel A. Alexandrov

  2. ITMO University, St. Petersburg, Russia

    Alexander V. Boukhanovsky

  3. ITMO University, St. Petersburg, Russia

    Andrei V. Chugunov

  4. National Research University Higher School of Economics, St. Petersburg, Russia

    Yury Kabanov

  5. National Research University Higher School of Economics, St. Petersburg, Russia

    Olessia Koltsova

  6. National Research University Higher School of Economics, St. Petersburg, Russia

    Ilya Musabirov

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Televnoy, A., Ivanov, S.E., Gorlushkina, N. (2020). Hybrid Method of Multiple Factor Data Clusterization. In: Alexandrov, D.A., Boukhanovsky, A.V., Chugunov, A.V., Kabanov, Y., Koltsova, O., Musabirov, I. (eds) Digital Transformation and Global Society. DTGS 2020. Communications in Computer and Information Science, vol 1242. Springer, Cham. https://doi.org/10.1007/978-3-030-65218-0_11

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  • DOI: https://doi.org/10.1007/978-3-030-65218-0_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-65217-3

  • Online ISBN: 978-3-030-65218-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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