Using Nested Surfaces for Visual Detection of Structures in Databases

  • Arturas Mazeika
  • Michael H. Böhlen
  • Peer Mylov
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4404)


We define, compute, and evaluate nested surfaces for the purpose of visual data mining. Nested surfaces enclose the data at various density levels, and make it possible to equalize the more and less pronounced structures in the data. This facilitates the detection of multiple structures, which is important for data mining where the less obvious relationships are often the most interesting ones. The experimental results illustrate that surfaces are fairly robust with respect to the number of observations, easy to perceive, and intuitive to interpret. We give a topology-based definition of nested surfaces and establish a relationship to the density of the data. Several algorithms are given that compute surface grids and surface contours, respectively.


Probability Density Function Density Level Visual Detection Grid Line Data Cube 
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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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Arturas Mazeika
    • 1
    • 2
  • Michael H. Böhlen
    • 1
  • Peer Mylov
    • 2
  1. 1.Faculty of Computer ScienceFree University of Bozen-BolzanoBozenItaly
  2. 2.Institute of CommunicationAalborg UniversityAalborgDenmark

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