VOS: A New Method for Visualizing Similarities Between Objects

  • Nees Jan van Eck
  • Ludo Waltman
Conference paper

DOI: 10.1007/978-3-540-70981-7_34

Part of the Studies in Classification, Data Analysis, and Knowledge Organization book series (STUDIES CLASS)
Cite this paper as:
van Eck N.J., Waltman L. (2007) VOS: A New Method for Visualizing Similarities Between Objects. In: Decker R., Lenz H.J. (eds) Advances in Data Analysis. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg

Abstract

We present a new method for visualizing similarities between objects. The method is called VOS, which is an abbreviation for visualization of similarities. The aim of VOS is to provide a low-dimensional visualization in which objects are located in such a way that the distance between any pair of objects reflects their similarity as accurately as possible. Because the standard approach to visualizing similarities between objects is to apply multidimensional scaling, we pay special attention to the relationship between VOS and multidimensional scaling.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Nees Jan van Eck
    • 1
  • Ludo Waltman
    • 1
  1. 1.Econometric Institute, Faculty of EconomicsErasmus University RotterdamRotterdamThe Netherlands

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