Exploratory spatio-temporal data mining and visualization

  title={Exploratory spatio-temporal data mining and visualization},
  author={P. Compieta and Sergio Di Martino and Michela Bertolotto and Filomena Ferrucci and M. Tahar Kechadi},
  journal={J. Vis. Lang. Comput.},
Spatio-temporal data sets are often very large and difficult to analyze and display. Since they are fundamental for decision support in many application contexts, recently a lot of interest has arisen toward data-mining techniques to filter out relevant subsets of very large data repositories as well as visualization tools to effectively display the results. In this paper we propose a data-mining system to deal with very large spatio-temporal data sets. Within this system, new techniques have… CONTINUE READING
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Publications referenced by this paper.
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  • M. F. Costabile
  • Malerba (Eds.), Special issue on visual data…
  • 2003
Highly Influential
6 Excerpts


  • U. M. Fayyad, G. G. Grinstein
  • in: Information Visualization in Data Mining and…
  • 2007
1 Excerpt

IEEE visualization 2004 contest

  • IEEE Computer Society
  • /http://vis.computer.org/vis2004contest/S
  • 2004
1 Excerpt

Special issue on visual data mining

  • D. Malerba M. F. Costabile
  • Journal of Visual Languages and Computing
  • 2003

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