Angle-Based Model for Interactive Dimensionality Reduction and Data Visualization

  • Cielo K. Basante-Villota
  • Carlos M. Ortega-CastilloEmail author
  • Diego F. Peña-Unigarro
  • E. Javier Revelo-Fuelagán
  • Jose A. Salazar-Castro
  • MacArthur Ortega-Bustamante
  • Paul Rosero-Montalvo
  • Laura Stella Vega-Escobar
  • Diego H. Peluffo-Ordóñez
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11047)


In recent times, an undeniable fact is that the amount of data available has increased dramatically due mainly to the advance of new technologies allowing for storage and communication of enormous volumes of information. In consequence, there is an important need for finding the relevant information within the raw data through the application of novel data visualization techniques that permit the correct manipulation of data. This issue has motivated the development of graphic forms for visually representing and analyzing high-dimensional data. Particularly, in this work, we propose a graphical approach, which, allows the combination of dimensionality reduction (DR) methods using an angle-based model, making the data visualization more intelligible. Such approach is designed for a readily use, so that the input parameters are interactively given by the user within a user-friendly environment. The proposed approach enables users (even those being non-experts) to intuitively select a particular DR method or perform a mixture of methods. The experimental results prove that the interactive manipulation enabled by the here-proposed model-due to its ability of displaying a variety of embedded spaces-makes the task of selecting a embedded space simpler and more adequately fitted for a specific need.


Dimensionality reduction Data visualization Kernel PCA Pairwise similarity 



This work is supported by the Smart Data Analysis Systems (SDAS) Research Group (, as well as the “Grupo de Investigación en Ingeniería Eléctrica y Electrónica - GIIEE” from Universidad de Nariño. Also, the authors acknowledge to the research project: “Desarrollo de una metodología de visualización interactiva y eficaz de información en Big Data” supported by Agreement No. 18 November 1st, 2016 by VIPRI from Universidad de Nariño.


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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Cielo K. Basante-Villota
    • 1
  • Carlos M. Ortega-Castillo
    • 1
    Email author
  • Diego F. Peña-Unigarro
    • 1
  • E. Javier Revelo-Fuelagán
    • 1
  • Jose A. Salazar-Castro
    • 1
    • 2
  • MacArthur Ortega-Bustamante
    • 3
  • Paul Rosero-Montalvo
    • 3
    • 4
    • 5
  • Laura Stella Vega-Escobar
    • 6
  • Diego H. Peluffo-Ordóñez
    • 2
    • 7
  1. 1.Universidad de NariñoPastoColombia
  2. 2.Corporación Universitaria Autónoma de NariñoPastoColombia
  3. 3.Universidad Técnica del NorteIbarraEcuador
  4. 4.Universidad de SalamancaSalamancaSpain
  5. 5.Instituto Tecnológico Superior 17 de JulioIbarraEcuador
  6. 6.Instituto Tecnológico Metropolitano (ITM)MedellínColombia
  7. 7.Yachay TechUrcuquíEcuador

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