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A New Incremental Algorithm for Overlapped Clustering

  • Airel Pérez Suárez
  • José Fco. Martínez Trinidad
  • Jesús A. Carrasco Ochoa
  • José E. Medina Pagola
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5856)

Abstract

In this paper, a new algorithm for incremental overlapped clustering, called Incremental Clustering by Strength Decision (ICSD), is introduced. ICSD obtains a set of dense and overlapped clusters using a new graph cover heuristic while reduces the amount of computation by maintaining incrementally the cluster structure. The experimental results show that our proposal outperforms other graph-based clustering algorithms considering quality measures and also show that ICSD achieves a better time performance than other incremental graph-based algorithms.

Keywords

Cluster Algorithm Document Collection Adjacent Vertex Star Cluster Cluster Document 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    Gil-García, R.J., Badía-Contelles, J.M., Pons-Porrata, A.: Extended Star Clustering Algorithm. In: Sanfeliu, A., Ruiz-Shulcloper, J. (eds.) CIARP 2003. LNCS, vol. 2905, pp. 480–487. Springer, Heidelberg (2003)Google Scholar
  2. 2.
    Pérez-Suárez, A., Medina-Pagola, J.E.: A Clustering Algorithm Based on Generalized Stars. In: Perner, P. (ed.) MLDM 2007. LNCS (LNAI), vol. 4571, pp. 248–262. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  3. 3.
    Gago-Alonso, A., Pérez-Suárez, A., Medina-Pagola, J.E.: ACONS: A New Algorithm for Clustering Documents. In: Rueda, L., Mery, D., Kittler, J. (eds.) CIARP 2007. LNCS, vol. 4756, pp. 664–673. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  4. 4.
    Pérez-Suárez, A., Martínez-Trinidad, J.F., Carrasco-Ochoa, J.A., Medina-Pagola, J.E.: A New Graph-Based Algorithm for Clustering Documents. In: ICDM-Workshops 2008, pp. 710–719 (2008)Google Scholar
  5. 5.
    Aslam, J., Pelekhov, E., Rus, D.: The star clustering algorithm for static and dynamic information organization. Journal of Graph Algorithms and Applications 8(1), 95–129 (2004)zbMATHMathSciNetGoogle Scholar
  6. 6.
    Pons-Porrata, A., Ruiz-Shulcloper, J., Berlanga-Llavori, R., Santiesteban-Alganza, Y.: Un algoritmo incremental para la obtención de cubrimientos con datos mezclados. In: CIARP 2002, pp. 405–416 (2002)Google Scholar
  7. 7.
    Pons-Porrata, A., Berlanga-Llavori, R., Ruiz-Shulcloper, J.: On-line event and topic detection by using the compact sets clustering algorithm. Journal of Intelligent and Fuzzy Systems 12(3), 185–194 (2002)zbMATHGoogle Scholar
  8. 8.
    Ruiz-Shulcloper, J., Sanchez, G., Abidi, M.A.: Clustering in mixed incomplete data. Heuristics and Optimization for Knowledge Discovery, 88–106 (2002)Google Scholar
  9. 9.
    Duda, R.O., Hart, P.E., Stork, D.G.: Pattern Classification. John Wiley & Sons Inc., New York (2001)zbMATHGoogle Scholar
  10. 10.
    Banerjee, A., Krumpelman, C., Basu, S., Mooney, R., Ghosh, J.: Model based overlapping clustering. In: KDD 2005, pp. 532–537 (2005)Google Scholar
  11. 11.
    Kuncheva, L., Hadjitodorov, S.: Using diversity in cluster ensembles. In: IEEE SMC 2004, The Netherlands, pp. 1214–1219 (2004)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Airel Pérez Suárez
    • 1
    • 2
  • José Fco. Martínez Trinidad
    • 1
  • Jesús A. Carrasco Ochoa
    • 1
  • José E. Medina Pagola
    • 2
  1. 1.National Institute for Astrophysics,Optics and Electronics (INAOE)Mexico
  2. 2.Advanced Technologies Application Center(CENATAV)Cuba

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