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The Visual Computer

, Volume 35, Issue 6–8, pp 1067–1080 | Cite as

The Visual SuperTree: similarity-based multi-scale visualization

  • Renato R. O. da SilvaEmail author
  • José Gustavo S. Paiva
  • Guilherme P. Telles
  • Carlos E. A. Zampieri
  • Fábio P. Rolli
  • Rosane Minghim
Original Article
  • 224 Downloads

Abstract

Similarity-based exploration of multi-dimensional data sets is a difficult task, in which most techniques do not perform well with large data sets, particularly in handling clutter that invariably happens as data sets grow larger. In this paper, we introduce the Visual SuperTree (VST), a method to build a multi-scale similarity tree that can deal with large data sets at interactive rates, maintaining most of the accuracy and the data organization capabilities of other available methods. The VST is built on top of a clustered multi-level configuration of the data that allows the user to quickly explore data sets by similarity. The method is shown to be useful for both unlabeled and labeled data, and it is capable of revealing external and internal cluster structures. We demonstrate its application on artificial and real data sets, showing additional advantages of the approach when exploring data that can be summarized meaningfully.

Keywords

Similarity trees Multi-dimensional data Multi-scale visualization Image and text visualization 

Notes

Acknowledgements

We would like to thank the reviewers for their helpful suggestions.

Funding

This work was funded by the São Paulo Research Foundation (FAPESP), Grant 2011/18838-5, and the National Council for Scientific and Technological Development (CNPq), Grants 307411/2016-8 and 310299/2018-7.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Supplementary material

Supplementary material 1 (mp4 9879 KB)

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.University of São PauloSão CarlosBrazil
  2. 2.Federal University of UberlândiaUberlândiaBrazil
  3. 3.University of CampinasCampinasBrazil
  4. 4.Federal University of Grande DouradosDouradosBrazil
  5. 5.University of GroningenGroningenThe Netherlands

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