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C&E Re-clustering: Reconstruction of Clustering Results by Three-Way Strategy

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Abstract

Many existing approaches to clustering are based on a two-way strategy that does not adequately show the fact that a cluster may not have a well-defined boundary. In this paper, we propose a Contraction and Expansion Re-clustering (C&E Re-clustering for short) model based on three-way strategy. The model utilizes the ideas of erosion and dilation in mathematical morphology. Contraction is used to shrink clusters while expansion is used to stretch clusters obtained by using an existing clustering algorithm. The difference between the results of contraction and expansion is regarded as the fringe region of the specific cluster. Therefore, a three-way explanation of the cluster is naturally formed. A C&E NJW re-clustering algorithm is proposed and the results on synthetic data set show that such a strategy is effective in improving the structure of clustering results.

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Acknowledgements

This work was supported in part by National Natural Science Foundation of China (Nos. 61503160 and 61572242), Natural Science Foundation of the Jiangsu Higher Education Institutions of China (No. 15KJB110004), and a Discovery Grant from NSERC, Canada.

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Authors and Affiliations

  1. School of Science, Jiangsu University of Science and Technology, Zhenjiang, 212003, China

    Pingxin Wang

  2. Department of Computer Science, University of Regina, Regina, SK, S4S 0A2, Canada

    Pingxin Wang, Xibei Yang & Yiyu Yao

  3. College of Mathematics and Information Science, Hebei Normal University, Shijiazhuang, 050024, China

    Pingxin Wang

  4. School of Computer Science, Jiangsu University of Science and Technology, Zhenjiang, 212003, China

    Xibei Yang

Authors
  1. Pingxin Wang
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  2. Xibei Yang
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  3. Yiyu Yao
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Corresponding author

Correspondence to Pingxin Wang .

Editor information

Editors and Affiliations

  1. Warsaw University of Technology, Warsaw, Poland

    Marzena Kryszkiewicz

  2. University of Bari Aldo Moro, Bari, Italy

    Annalisa Appice

  3. Institute of Informatics, University of Warsaw, Warsaw, Poland

    Dominik Ślęzak

  4. Faculty of Electronics & Information, Warsaw University of Technology, Warsaw, Poland

    Henryk Rybinski

  5. Institute of Mathematics, Warsaw University, Warsaw, Poland

    Andrzej Skowron

  6. Department of Computer Science, University of North Carolina at Charlotte, North Carolina, USA

    Zbigniew W. RaÅ›

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Wang, P., Yang, X., Yao, Y. (2017). C&E Re-clustering: Reconstruction of Clustering Results by Three-Way Strategy. In: Kryszkiewicz, M., Appice, A., Ślęzak, D., Rybinski, H., Skowron, A., Raś, Z. (eds) Foundations of Intelligent Systems. ISMIS 2017. Lecture Notes in Computer Science(), vol 10352. Springer, Cham. https://doi.org/10.1007/978-3-319-60438-1_53

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  • DOI: https://doi.org/10.1007/978-3-319-60438-1_53

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-60437-4

  • Online ISBN: 978-3-319-60438-1

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