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Temporary User Modeling for Adaptive Product Presentations in the Web

  • Tanja Joerding
Part of the CISM International Centre for Mechanical Sciences book series (CISM, volume 407)

Abstract

This work proposes a temporary user modeling approach that enables the immediate adaptation of product presentations in the Web to the individual customer at runtime by using a machine learning algorithm. We focus on the question of how monitored user interactions can be preprocessed to get example data for the learning algorithm and how existing decision tree or decision list algorithms fit the requirements of the new application field of electronic shopping.

Keywords

Learning Algorithm User Modeling Product Presentation Temporary User Presentation Element 
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.

References

  1. Joerding, T., and Meissner, K. (1998), Intelligent Multimedia Presentations in the Web: Fun without Annoyance. In: Proccedings of the Seventh International World Wide Web Conference, Brisbane, Australia, 649–650.Google Scholar
  2. Joerding, T., and Michel, S. (1999), Personalized Shopping in the Web by Monitoring the Customer. In: Proceedings of The Active WebA British HCI Group Day Conference, Stafford, UK.Google Scholar
  3. Shen, W.M. (1996), An Efficient Algorithm for Incremental Learning of Decision Lists. Technical Report, USC-ISI-96–012, Information Sciences Institute, University of Southern California, http://www.isi.edu/~shen/papers_by_date.htmlGoogle Scholar

Copyright information

© Springer Science+Business Media New York 1999

Authors and Affiliations

  • Tanja Joerding
    • 1
  1. 1.Department of Computer ScienceDresden University of TechnologyGermany

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