3D visual data mining: goals and experiences

  • Authors:
  • Michael Böhlen;Linas Bukauskas;Poul Svante Eriksen;Steffen Lilholt Lauritzen;Arturas Mažeika;Peter Musaeus;Peer Mylov

  • Affiliations:
  • Department of Computer Science, Aalborg University, Frederik Bajers Vej 7E, Aalborg 9220, Denmark;Department of Computer Science, Aalborg University, Frederik Bajers Vej 7E, Aalborg 9220, Denmark;Department of Computer Science, Aalborg University, Frederik Bajers Vej 7E, Aalborg 9220, Denmark;Department of Computer Science, Aalborg University, Frederik Bajers Vej 7E, Aalborg 9220, Denmark;Department of Computer Science, Aalborg University, Frederik Bajers Vej 7E, Aalborg 9220, Denmark;Department of Computer Science, Aalborg University, Frederik Bajers Vej 7E, Aalborg 9220, Denmark;Department of Computer Science, Aalborg University, Frederik Bajers Vej 7E, Aalborg 9220, Denmark

  • Venue:
  • Computational Statistics & Data Analysis - Data visualization
  • Year:
  • 2003

Quantified Score

Hi-index 0.00

Visualization

Abstract

The visual exploration of large databases raises a number of unresolved inference problems and calls for new interaction patterns between multiple disciplines--both at the conceptual and technical level. We present an approach that is based on the interaction of four disciplines: database systems, statistical analyses, perceptual and cognitive psychology, and scientific visualization. At the conceptual level we offer perceptual and cognitive insights to guide the information visualization process. We then choose cluster surfaces to exemplify the data mining process, to discuss the tasks involved, and to work out the interaction patterns.