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A Discussion on Visual Interactive Data Exploration Using Self-Organizing Maps

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Part of the Lecture Notes in Computer Science book series (LNTCS,volume 6731)

Abstract

In recent years, a variety of visualization techniques for visual data exploration based on self-organizing maps (SOMs) have been developed. To support users in data exploration tasks, a series of software tools emerged which integrate various visualizations. However, the focus of most research was the development of visualizations which improve the support in cluster identification. In order to provide real insight into the data set it is crucial that users have the possibility of interactively investigating the data set. This work provides an overview of state-of-the-art software tools for SOM-based visual data exploration. We discuss the functionality of software for specialized data sets, as well as for arbitrary data sets with a focus on interactive data exploration.

Keywords

  • Feature Vector
  • Augmented Reality
  • Data Exploration
  • Visualization Technique
  • Interaction Technique

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.

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Moehrmann, J., Burkovski, A., Baranovskiy, E., Heinze, GA., Rapoport, A., Heidemann, G. (2011). A Discussion on Visual Interactive Data Exploration Using Self-Organizing Maps. In: Laaksonen, J., Honkela, T. (eds) Advances in Self-Organizing Maps. WSOM 2011. Lecture Notes in Computer Science, vol 6731. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21566-7_18

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  • DOI: https://doi.org/10.1007/978-3-642-21566-7_18

  • Publisher Name: Springer, Berlin, Heidelberg

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