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Clustering Ensemble Using ANT and ART

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Swarm Intelligence in Data Mining

Part of the book series: Studies in Computational Intelligence ((SCI,volume 34))

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Author information

Authors and Affiliations

  1. School of Information Science and Technology, Southwest Jiaotong University, 610031, Chengdu, Sichuan, China

    Yan Yang

  2. Pattern Analysis and Machine Intelligence Lab, Electrical and Computer Engineering, University of Waterloo, N2L 3G1, Waterloo, Ontario, Canada

    Mohamed Kamel

  3. School of Information Science and Technology, Southwest Jiaotong University, 610031, Chengdu, Sichuan, China

    Fan Jin

Authors
  1. Yan Yang
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  2. Mohamed Kamel
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  3. Fan Jin
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Editor information

Editors and Affiliations

  1. IITA Professorship Program, School of Computer Science and Engineering Chung-Ang University, 221 Heukseok-dong, 156-756, Dongjak-gu Seoul, Republic of Korea

    Ajith Abraham

  2. Department of Computer Science, Faculty of Mathematics and Computer Science, Babes-Bolyai University, Cluj-Napoca, Kogalniceanu 1, 400084, Cluj - Napoca, Romania

    Crina Grosan

  3. CVRM-IST, IST, Technical University of Lisbon, Av. Rovisco Pais, 1049-001, Lisboa, Portugal

    Vitorino Ramos

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© 2006 Springer-Verlag Berlin Heidelberg

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Yang, Y., Kamel, M., Jin, F. (2006). Clustering Ensemble Using ANT and ART. In: Abraham, A., Grosan, C., Ramos, V. (eds) Swarm Intelligence in Data Mining. Studies in Computational Intelligence, vol 34. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-34956-3_11

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  • DOI: https://doi.org/10.1007/978-3-540-34956-3_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-34955-6

  • Online ISBN: 978-3-540-34956-3

  • eBook Packages: EngineeringEngineering (R0)

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