Eigensolver Methods for Progressive Multidimensional Scaling of Large Data

  • Ulrik Brandes
  • Christian Pich
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4372)

Abstract

We present a novel sampling-based approximation technique for classical multidimensional scaling that yields an extremely fast layout algorithm suitable even for very large graphs. It produces layouts that compare favorably with other methods for drawing large graphs, and it is among the fastest methods available. In addition, our approach allows for progressive computation, i.e. a rough approximation of the layout can be produced even faster, and then be refined until satisfaction.

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Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  • Ulrik Brandes
    • 1
  • Christian Pich
    • 1
  1. 1.Department of Computer & Information Science, University of KonstanzGermany

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