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Alluvial SOTM: Visualizing Transitions and Changes in Cluster Structure of the Self-Organizing Time Map

Samuel Rönnqvist, Peter Sarlin, Alluvial SOTM: Visualizing Transitions and Changes in Cluster Structure of the Self-Organizing Time Map. In: Robert S Laramee, Min Chen (Eds.), The Eurographics Conference on Visualization (EuroVis), Eurographics, 2014.

Abstract:

We present the Alluvial SOTM as a visualization design for the Self-Organizing Time Map (SOTM), an algorithm providing means for visual dynamic clustering. The Alluvial SOTM improves upon previous SOTM visualizations by illustrating the distribution and movement of data points across clusters in time. Transition patterns and vol-
umes are shown using alluvial diagrams, while individual data points can be tracked through interaction. In addition, we show how the vertical dimension of the diagram can be used to depict structural change among clusters and drift in data across cross sections.

BibTeX entry:

@INPROCEEDINGS{inpRxSa14b,
  title = {Alluvial SOTM: Visualizing Transitions and Changes in Cluster Structure of the Self-Organizing Time Map},
  booktitle = {The Eurographics Conference on Visualization (EuroVis)},
  author = {Rönnqvist, Samuel and Sarlin, Peter},
  editor = {Laramee, Robert S and Chen, Min},
  publisher = {Eurographics},
  year = {2014},
}

Belongs to TUCS Research Unit(s): Data Mining and Knowledge Management Laboratory

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