Temporal extrapolation within a static clustering

  • Authors:
  • Tim K. Cocx;Walter A. Kosters;Jeroen F. J. Laros

  • Affiliations:
  • Leiden Institute of Advanced Computer Science, Leiden University, The Netherlands;Leiden Institute of Advanced Computer Science, Leiden University, The Netherlands;Leiden Institute of Advanced Computer Science, Leiden University, The Netherlands

  • Venue:
  • ISMIS'08 Proceedings of the 17th international conference on Foundations of intelligent systems
  • Year:
  • 2008

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Abstract

Predicting the behaviour of individuals is a core business of policy makers. This paper discusses a new way of predicting the "movement in time" of items through pre-defined classes by analysing their changing placement within a static, preconstructed 2-dimensional clustering. It employs the visualization realized in previous steps within item analysis, rather than performing complex calculations on each attribute of each item. For this purpose we adopt a range of well-known mathematical extrapolation methods that we adapt to fit our need for 2-dimensional extrapolation. Usage of the approach on a criminal record database to predict evolvement of criminal careers, shows some promising results.