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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 423–430Cite as

A Novel Possibilistic Fuzzy Leader Clustering Algorithm

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

Abstract

The clusters tend to have vague or imprecise boundaries in some fields such as web mining, since clustering has been widely used. Fuzzy clustering is sensitive to noises and possibilistic clustering is sensitive to the initialization of cluster centers and generates coincident clusters. Based on combination of fuzzy clustering and possibilistic clustering, a novel possibilistic fuzzy leader (PFL) clustering algorithm is proposed in this paper to overcome these shortcomings. Considering the advantages of the leader algorithm in time efficiency and the initialization of cluster, the framework of the leader algorithm is used. In addition, a λ-cut set is defined to process the overlapping clusters adaptively. The comparison of experimental results shows that our proposed algorithm is valid, efficient, and has better accuracy.

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Author information

Authors and Affiliations

  1. Institute of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, 400065, P.R. China

    Hong Yu & Hu Luo

Authors
  1. Hong Yu
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  2. Hu Luo
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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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Cite this paper

Yu, H., Luo, H. (2009). A Novel Possibilistic Fuzzy Leader Clustering Algorithm. 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_51

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  • DOI: https://doi.org/10.1007/978-3-642-10646-0_51

  • 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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