The Dissimilarity Representation as a Tool for Three-Way Data Classification: A 2D Measure

  • Diana Porro-Muñoz
  • Robert P. W. Duin
  • Mauricio Orozco-Alzate
  • Isneri Talavera
  • John Makario Londoño-Bonilla
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6218)


The dissimilarity representation has demonstrated advantages in the solution of classification problems. Meanwhile, the representation of objects by multi-dimensional arrays is necessary in many research areas. However, the development of proper classification tools that take the multi-way structure into account is incipient. This paper introduces the use of the dissimilarity representation as a tool for classifying three-way data, as dissimilarities allow the representation of multi-dimensional objects in a natural way. As an example, the classification of three-way seismic volcanic data is used. A comparison is made between dissimilarity measures used in different representations of the three-way data. 2D dissimilarity measures for three-way data can be useful.


Object representation classification multi-dimensional data dissimilarity representation 


  1. 1.
    Porro-Muñoz, D., Talavera, I., Duin, R.P.W.: Multi-way data analysis. Technical report, CENATAV (2009)Google Scholar
  2. 2.
    Kroonenberg, P.M.: Applied Multiway Data Analysis. John Wiley & Sons, Chichester (2008)zbMATHCrossRefGoogle Scholar
  3. 3.
    Pekalska, E., Duin, R.P.W.: The Dissimilarity Representation For Pattern Recognition. In: Foundations and Applications, World Scientific, Singapore (2005)Google Scholar
  4. 4.
    Orozco-Alzate, M., García, M.E., Duin, R.P.W., Castellanos, C.G.: Dissimilarity-based classification of seismic signals at Nevado del Ruiz Volcano. Earth Sci. Res. J. 10(2), 57–65 (2006)Google Scholar
  5. 5.
    Paclik, P., Duin, R.P.W.: Dissimilarity-based classification of spectra: computational issues. Real Time Imaging 9(4), 237–244 (2003)CrossRefGoogle Scholar
  6. 6.
    Benbrahim, M., Daoudi, A., Benjelloun, K., Ibenbrahim, A.: Discrimination of seismic signals using artificial neural networks. In: Ardil, C. (ed.) WEC (2), Enformatika, Çanakkale, Turkey, vol. (2), pp. 4–7 (2005)Google Scholar
  7. 7.
    Lesage, P., Glangeau, F., Mars, J.: Applications of autoregressive models and time-frequency analysis to the study of volcanic tremor and long-period events. Journal of Volcanology and Geothermal Research 114, 391–417 (2002)CrossRefGoogle Scholar
  8. 8.
    Curilem, G., Vergara, J., Fuentealba, G., Acuña, G., Chacón, M.: Classification of seismic signals at Villarrica Volcano (Chile) using neural networks and genetic algorithms. Journal of Volcanology and Geothermal Research 180(1), 1–8 (2009)CrossRefGoogle Scholar
  9. 9.
    Zobin, V.M.: Introduction to Volcanic Seismology. Developments in Volcanology, vol. 6. Elsevier, Philadelphia (2003)Google Scholar
  10. 10.
    Zuo, W., Zhang, D., Wang, K.: An assembled matrix distance metric for 2DPCA-based image recognition. Pattern Recognition Letters 27, 210–216 (2006)Google Scholar
  11. 11.
    Lesage, P.: Interactive Matlab software for the analysis of seismic volcanic signals. Computers & Geosciences 114, 391–417 (2009)Google Scholar
  12. 12.
    Orozco-Alzate, M., Skurichina, M., Duin, R.P.W.: Spectral characterization of volcanic earthquakes at Nevado del Ruiz Volcano using spectral band selection/extraction techniques. In: Ruiz-Shulcloper, J., Kropatsch, W.G. (eds.) CIARP 2008. LNCS, vol. 5197, pp. 708–715. Springer, Heidelberg (2008)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Diana Porro-Muñoz
    • 1
    • 2
  • Robert P. W. Duin
    • 2
  • Mauricio Orozco-Alzate
    • 3
  • Isneri Talavera
    • 1
  • John Makario Londoño-Bonilla
    • 4
  1. 1.Advanced Technologies Application Center (Cenatav)Cuba
  2. 2.Pattern Recognition LabTU DelftThe Netherlands
  3. 3.Universidad Nacional de Colombia Sede ManizalesColombia
  4. 4.Instituto Colombiano de Geología y Minería (Ingeominas)Colombia

Personalised recommendations