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A Novel Color-Based Data Visualization Approach Using a Circular Interaction Model and Dimensionality Reduction

  • Jose Alejandro Salazar-Castro
  • Paul D. Rosero-Montalvo
  • Diego Fernando Peña-Unigarro
  • Ana Cristina Umaquinga-Criollo
  • Zenaida Castillo-Marrero
  • Edgardo Javier Revelo-Fuelagán
  • Diego Hernán Peluffo-Ordóñez
  • César Germán Castellanos-Domínguez
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10878)

Abstract

Dimensionality reduction (DR) methods are able to produce low-dimensional representations of an input data sets which may become intelligible for human perception. Nonetheless, most existing DR approaches lack the ability to naturally provide the users with the faculty of controlability and interactivity. In this connection, data visualization (DataVis) results in an ideal complement. This work presents an integration of DR and DataVis through a new approach for data visualization based on a mixture of DR resultant representations while using visualization principle. Particularly, the mixture is done through a weighted sum, whose weighting factors are defined by the user through a novel interface. The interface’s concept relies on the combination of the color-based and geometrical perception in a circular framework so that the users may have a at hand several indicators (shape, color, surface size) to make a decision on a specific data representation. Besides, pairwise similarities are plotted as a non-weighted graph to include a graphic notion of the structure of input data. Therefore, the proposed visualization approach enables the user to interactively combine DR methods, while providing information about the structure of original data, making then the selection of a DR scheme more intuitive.

Keywords

Data visualization Dimensionality reduction Interactive interface Pairwise similarity 

Notes

Acknowledgments

This work is supported by the “Smart Data Analysis Systems - SDAS” group (http://sdas-group.com). Also, authors acknowledge to the research project “Desarrollo de una metodología de visualizaciń interactiva y eficaz de información en Big Data” supported by Agreement No. 180 November 1st, 2016 by VIPRI, as well as “Grupo de Investigación en Ingeniería Eléctrica y Electrónica - GIIEE”, from Universidad de Nariño.

References

  1. 1.
    Díaz, I., Cuadrado, A.A., Pérez, D., García, F.J., Verleysen, M.: Interactive dimensionality reduction for visual analytics. In: Proceedings of the 22th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2014), pp. 183–188. Citeseer (2014)Google Scholar
  2. 2.
    Fukunaga, K.: Introduction to Statistical Pattern Recognition. Academic Press, Cambridge (2013)zbMATHGoogle Scholar
  3. 3.
    Lee, J.A., Renard, E., Bernard, G., Dupont, P., Verleysen, M.: Type 1 and 2 mixtures of Kullback-Leibler divergences as cost functions in dimensionality reduction based on similarity preservation. Neurocomputing 112, 92–108 (2013)CrossRefGoogle Scholar
  4. 4.
    Peluffo-Ordóñez, D.H., Lee, J.A., Verleysen, M.: Short review of dimensionality reduction methods based on stochastic neighbour embedding. In: Villmann, T., Schleif, F.-M., Kaden, M., Lange, M. (eds.) Advances in Self-Organizing Maps and Learning Vector Quantization. AISC, vol. 295, pp. 65–74. Springer, Cham (2014).  https://doi.org/10.1007/978-3-319-07695-9_6CrossRefGoogle Scholar
  5. 5.
    Peluffo-Ordóñez, D.H., Lee, J.A., Verleysen, M.: Generalized kernel framework for unsupervised spectral methods of dimensionality reduction. In: 2014 IEEE Symposium on Computational Intelligence and Data Mining (CIDM), pp. 171–177. IEEE (2014)Google Scholar
  6. 6.
    Peluffo Ordoñez, D.H., Lee, J.A., Verleysen, M., et al.: Recent methods for dimensionality reduction: a brief comparative analysis. In: 2014 European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2014) (2014)Google Scholar
  7. 7.
    Peña-Unigarro, D.F., Rosero-Montalvo, P., Revelo-Fuelagán, E.J., Castro-Silva, J.A., Alvarado-Pérez, J.C., Therón, R., Ortega-Bustamante, C.M., Peluffo-Ordóñez, D.H.: Interactive data visualization using dimensionality reduction and dissimilarity-based representations. In: Yin, H., et al. (eds.) IDEAL 2017. LNCS, vol. 10585, pp. 461–469. Springer, Cham (2017).  https://doi.org/10.1007/978-3-319-68935-7_50CrossRefGoogle Scholar
  8. 8.
    Peña-ünigarro, D.F., Salazar-Castro, J.A., Peluffo-Ordóñez, D.H., Rosero-Montalvo, P.D., Oña-Rocha, O.R., Isaza, A.A., Alvarado-Perez, J.C., Theron, R.: Interactive visualization methodology of high-dimensional data with a color-based model for dimensionality reduction. In: 2016 XXI Symposium on Signal Processing, Images and Artificial Vision (STSIVA), pp. 1–7. IEEE (2016)Google Scholar
  9. 9.
    Rosero-Montalvo, P., Diaz, P., Salazar-Castro, J.A., Peña-Unigarro, D.F., Anaya-Isaza, A.J., Alvarado-Pérez, J.C., Therón, R., Peluffo-Ordóñez, D.H.: Interactive data visualization using dimensionality reduction and similarity-based representations. In: Beltrán-Castañón, C., Nyström, I., Famili, F. (eds.) CIARP 2016. LNCS, vol. 10125, pp. 334–342. Springer, Cham (2017).  https://doi.org/10.1007/978-3-319-52277-7_41CrossRefGoogle Scholar
  10. 10.
    Salazar-Castro, J., Rosas-Narváez, Y., Pantoja, A., Alvarado-Pérez, J.C., Peluffo-Ordóñez, D.H.: Interactive interface for efficient data visualization via a geometric approach. In: 2015 XX Symposium on Signal Processing, Images and Computer Vision (STSIVA), pp. 1–6. IEEE (2015)Google Scholar
  11. 11.
    Sedlmair, M., Munzner, T., Tory, M.: Empirical guidance on scatterplot and dimension reduction technique choices. IEEE Trans. Vis. Comput. Graph. 19(12), 2634–2643 (2013)CrossRefGoogle Scholar
  12. 12.
    Ward, M.O., Grinstein, G., Keim, D.: Interactive Data Visualization: Foundations, Techniques, and Applications. CRC Press, Boca Raton (2010)zbMATHGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Jose Alejandro Salazar-Castro
    • 1
    • 2
  • Paul D. Rosero-Montalvo
    • 3
    • 4
    • 5
  • Diego Fernando Peña-Unigarro
    • 6
  • Ana Cristina Umaquinga-Criollo
    • 3
    • 4
  • Zenaida Castillo-Marrero
    • 5
  • Edgardo Javier Revelo-Fuelagán
    • 6
  • Diego Hernán Peluffo-Ordóñez
    • 1
    • 5
  • César Germán Castellanos-Domínguez
    • 2
  1. 1.Coorporación Universitaria Autónoma de NariñoPastoColombia
  2. 2.Universidad Nacional sede ManizalesManizalesColombia
  3. 3.Universidad Técnica del NorteIbarraEcuador
  4. 4.Universidad de SalamancaSalamancaSpain
  5. 5.Yachay TechUrcuquíEcuador
  6. 6.Universidad de NariñoPastoColombia

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