VOS: A New Method for Visualizing Similarities Between Objects

  • Nees Jan van Eck
  • Ludo Waltman
Part of the Studies in Classification, Data Analysis, and Knowledge Organization book series (STUDIES CLASS)

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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. BORG, I. and GROENEN, P.J.F. (2005): Modern Multidimensional Scaling. Springer, Berlin.MATHGoogle Scholar
  2. DAVIDSON, G.S., HENDRICKSON, B., JOHNSON, D.K., MEYERS, C.E. and WYLIE, B.N. (1998): Knowledge Mining with VxInsight: Discovery through Interaction. Journal of Intelligent Information Systems, 11, 259–285.CrossRefGoogle Scholar
  3. KENDALL, D.G. (1971): Seriation from Abundance Matrices. In: F.R. Hodson, D.G. Kendall and P. Tautu (Eds.): Mathematics in the Archaeological and Historical Sciences. Edinburgh University Press, 215–252.Google Scholar
  4. MARDIA, K.V., KENT, J.T. and BIBBY, J.M. (1979): Multivariate Analysis. Academic Press.Google Scholar
  5. SAMMON, J.W. (1969): A Nonlinear Mapping for Data Structure Analysis. IEEE Transactions on Computers, C-18,5, 401–409.CrossRefGoogle Scholar
  6. VAN DEN BERG, J., VAN ECK, N.J., WALTMAN, L. and KAYMAK, U. (2004): A VICORE Architecture for Intelligent Knowledge Management. In: Proceedings of the KDNet Symposium on Knowledge-Based Services for the Public Sector, 63–74.Google Scholar
  7. VAN ECK, N.J. and WALTMAN, L. (2006): VOS: A New Method for Visualizing Similarities Between Objects. Technical Report ERS-2006-020-LIS, Erasmus University Rotterdam, Erasmus Research Institute of Management.Google Scholar
  8. VAN ECK, N.J., WALTMAN, L. and VAN DEN BERG, J. (2005): A Novel Algorithm for Visualizing Concept Associations. In: Proceedings of the 16th International Workshop on Database and Expert Systems Applications, 405–409.Google Scholar
  9. VAN ECK, N.J., WALTMAN, L., VAN DEN BERG, J. and KAYMAK, U. (2006a): Visualizing the WCCI 2006 Knowledge Domain. In: Proceedings of the 2006 IEEE International Conference on Fuzzy Systems, 7862–7869.Google Scholar
  10. VAN ECK, N.J., WALTMAN, L., VAN DEN BERG, J. and KAYMAK, U. (2006b): Visualizing the Computational Intelligence Field. IEEE Computational Intelligence Magazine. Accepted for publication.Google Scholar

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

Personalised recommendations