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Distributed Algorithm for Text Documents Clustering Based on k-Means Approach

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Information Systems Architecture and Technology: Proceedings of 36th International Conference on Information Systems Architecture and Technology – ISAT 2015 – Part II

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 430))

Abstract

The presented paper describes the design and implementation of distributed k-means clustering algorithm for text documents analysis. Motivation for the research effort presented in this paper is to propose a distributed approach based on current in-memory distributed computing technologies. We have used our Jbowl java text mining library and GridGain as a framework for distributed computing. Using these technologies we have designed and implemented k-means distributed clustering algorithm in two modifications and performed the experiments on the standard text data collections. Experiments were conducted in two testing environments—a distributed computing infrastructure and on a multi-core server.

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Notes

  1. 1.

    http://sourceforge.net/projects/jbowl/.

  2. 2.

    http://www.gridgain.com/.

References

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Acknowledgements

The work presented in this paper was partially supported by the Slovak Grant Agency of Ministry of Education and Academy of Science of the Slovak Republic under grant No. 1/1147/12 (50 %) and as the result of the Project implementation: University Science Park TECHNICOM for Innovation Applications Supported by Knowledge Technology, ITMS: 26220220182, supported by the Research & Development Operational Programme funded by the ERDF (50 %).

Author information

Authors and Affiliations

  1. Department of Cybernetics and Artificial Intelligence, Faculty of Electrotechnics and Informatics, Technical University Kosice, Letna 9/a, 04001, Kosice, Slovakia

    Martin Sarnovsky & Noema Carnoka

Authors
  1. Martin Sarnovsky
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  2. Noema Carnoka
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Corresponding author

Correspondence to Martin Sarnovsky .

Editor information

Editors and Affiliations

  1. Faculty of Computer Science and Manageme, Wrocław University of Technology, Wrocła, Wrocław, Poland

    Adam Grzech

  2. Faculty of Computer Science and Manageme, Wrocław University of Technology, Wrocła, Wroclaw, Poland

    Leszek Borzemski

  3. Faculty of Computer Science and Manageme, Wrocław University of Technology, Wrocła, Wrocław, Poland

    Jerzy Świątek

  4. Faculty of Computer Science and Manageme, Wrocław University of Technology, Wrocła, Wrocław, Poland

    Zofia Wilimowska

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Sarnovsky, M., Carnoka, N. (2016). Distributed Algorithm for Text Documents Clustering Based on k-Means Approach. In: Grzech, A., Borzemski, L., Świątek, J., Wilimowska, Z. (eds) Information Systems Architecture and Technology: Proceedings of 36th International Conference on Information Systems Architecture and Technology – ISAT 2015 – Part II. Advances in Intelligent Systems and Computing, vol 430. Springer, Cham. https://doi.org/10.1007/978-3-319-28561-0_13

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  • DOI: https://doi.org/10.1007/978-3-319-28561-0_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-28559-7

  • Online ISBN: 978-3-319-28561-0

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