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Finding and Evaluating Fuzzy Clusters in Networks

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Book cover Advances in Swarm Intelligence (ICSI 2010)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6146))

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Abstract

Fuzzy cluster validity criterion tends to evaluate the quality of fuzzy partitions produced by fuzzy clustering algorithms. In this paper, an effective validity index for network fuzzy clustering is proposed, which involves the compactness and separation measures for each cluster. The simulated annealing strategy is used to minimize this validity index, associating with a dissimilarity-index-based fuzzy c-means iterative procedure, under the framework of a random walker Markovian dynamics on the network. The proposed algorithm (SADIF) can efficiently identify the probabilities of each node belonging to different clusters during the cooling process. An appropriate number of clusters can be automatically determined without any prior knowledge about the network structure. The computational results on several artificial and real-world networks confirm the capability of the algorithm.

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Author information

Authors and Affiliations

  1. LMAM and School of Mathematical Sciences, Peking University, Beijing, 100871, P.R. China

    Jian Liu

Authors
  1. Jian Liu
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Editor information

Editors and Affiliations

  1. Key Laboratory of Machine Perception (MOE), Department of Machine Intelligence, Peking University, 100871, Beijing, China

    Ying Tan

  2. Research and Postgraduate Office, Xi’an Jiaotong-Liverpool University, 215123, Suzhoum, China

    Yuhui Shi

  3. Department of Electrical and Computer Engineering, Engineering Drive 3, 4 Engineering Drive 3, National University of Singapore, 117576, Singapore

    Kay Chen Tan

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© 2010 Springer-Verlag Berlin Heidelberg

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Liu, J. (2010). Finding and Evaluating Fuzzy Clusters in Networks. In: Tan, Y., Shi, Y., Tan, K.C. (eds) Advances in Swarm Intelligence. ICSI 2010. Lecture Notes in Computer Science, vol 6146. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13498-2_3

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  • DOI: https://doi.org/10.1007/978-3-642-13498-2_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-13497-5

  • Online ISBN: 978-3-642-13498-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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