User Modelling for Interactive User-Adaptive Collection Structuring

  • Andreas Nürnberger
  • Sebastian Stober
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4918)


Automatic structuring is one means to ease access to document collections, be it for organization or for exploration. Of even greater help would be a presentation that adapts to the user’s way of structuring and thus is intuitively understandable. We extend an existing user-adaptive prototype system that is based on a growing self-organizing map and that learns a feature weighting scheme from a user’s interaction with the system resulting in a personalized similarity measure. The proposed approach for adapting the feature weights targets certain problems of previously used heuristics. The revised adaptation method is based on quadratic optimization and thus we are able to pose certain contraints on the derived weighting scheme. Moreover, thus it is guaranteed that an optimal weighting scheme is found if one exists. The proposed approach is evaluated by simulating user interaction with the system on two text datasets: one artificial data set that is used to analyze the performance for different user types and a real world data set – a subset of the banksearch dataset – containing additional class information.


Feature Weight Vector Space Model Adaptation Algorithm Quadratic Optimization Greedy Heuristic 
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

  • Andreas Nürnberger
    • 1
  • Sebastian Stober
    • 1
  1. 1.Institute for Knowledge and Language Engineering, Faculty of Computer ScienceOtto-von-Guericke-University MagdeburgMagdeburgGermany

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