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International Workshop on Rough Sets, Fuzzy Sets, Data Mining, and Granular-Soft Computing

RSFDGrC 2009: Rough Sets, Fuzzy Sets, Data Mining and Granular Computing pp 398–405Cite as

Interval Set Cluster Analysis: A Re-formulation

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5908))

Abstract

A new clustering strategy is proposed based on interval sets, which is an alternative formulation different from the ones used in the existing studies. Instead of using a single set as the representation of a cluster, each cluster is represented by an interval set that is defined by a pair of sets called the lower and upper bounds. Elements in the lower bound are typical elements of the cluster and elements between the upper and lower bounds are fringe elements of the cluster. A cluster is therefore more realistically characterized by a set of core elements and a set of boundary elements. Two types of interval set clusterings are proposed, one is non-overlapping lower bound interval set clustering and the other is overlapping lower bound interval set clusterings, corresponding to the standard partition based and covering based clusterings.

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Author information

Authors and Affiliations

  1. Department of Computer Science, University of Regina, Regina, Saskatchewan, Canada, S4S 0A2

    Yiyu Yao

  2. Department of Mathematics and Computing Science, Saint Mary’s University, Halifax, Nova Scotia, Canada, B3H 3C3

    Pawan Lingras

  3. Department of Computer Science and Technology, The Key Laboratory of Embedded System and Service Computing, Tongji University, Shanghai, 201804, P.R. China

    Ruizhi Wang & Duoqian Miao

Authors
  1. Yiyu Yao
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  2. Pawan Lingras
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  3. Ruizhi Wang
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  4. Duoqian Miao
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Editor information

Editors and Affiliations

  1. Department of Mathematics and Computer Aided Sciences, Kyushu Institute of Technology, 804-8550, Tobata, Kitakyushu, Japan

    Hiroshi Sakai

  2. Department of Pure Mathematics, University of Calcutta, 35 Ballygunge Circular Road, 700019, Kolkata, India

    Mihir Kumar Chakraborty

  3. Information Technology Department, University of Cairo, 5 Ahmed Zewal St. Orman, Giza, Egypt

    Aboul Ella Hassanien

  4. University of Warsaw & Infobright Inc., Poland

    Dominik Ślęzak

  5. University of Electronic Science and Technology of China, Chengdu, China

    William Zhu

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© 2009 Springer-Verlag Berlin Heidelberg

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Yao, Y., Lingras, P., Wang, R., Miao, D. (2009). Interval Set Cluster Analysis: A Re-formulation. In: Sakai, H., Chakraborty, M.K., Hassanien, A.E., Ślęzak, D., Zhu, W. (eds) Rough Sets, Fuzzy Sets, Data Mining and Granular Computing. RSFDGrC 2009. Lecture Notes in Computer Science(), vol 5908. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10646-0_48

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  • DOI: https://doi.org/10.1007/978-3-642-10646-0_48

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-10645-3

  • Online ISBN: 978-3-642-10646-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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