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Exploiting Learning Techniques for the Acquisition of User Stereotypes and Communities

  • Georgios Paliouras
  • Vangelis Karkaletsis
  • Christos Papatheodorou
  • Constantine D. Spyropoulos
Part of the CISM International Centre for Mechanical Sciences book series (CISM, volume 407)

Abstract

In this paper we examine the acquisition of user stereotypes and communities automatically from users’ data. Stereotypes are built using supervised learning (C4.5) on personal data extracted from a set of questionnaires answered by the users of a news filtering system. Particular emphasis is given to the characteristic features of the task of learning stereotypes and, in this context, the new notion of community stereotype is introduced. On the other hand, the communities are built using unsupervised learning (COBWEB) on data containing users’ interests on the news categories covered by the news filtering system. Our main concern is whether meaningful communities can be constructed and for this purpose we specify a metric to decide on the representative news categories for each community. The encouraging results presented in this paper, suggest that established machine learning methods can be particularly useful for the acquisition of stereotypes and communities.

Keywords

User Model Machine Learning Method Unsupervised Learning User Community User Class 
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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References

  1. Benaki, E., Karkaletsis, V. and Spyropoulos, C. D. (1997). Integrating User Modeling into Information Extraction: the UMIE Prototype. In Proceedings of the Sixth User Modeling Conference, 55–57.Google Scholar
  2. Bloedorn, E., Mani, I. and MacMillan, T. R. (1997). Machine Learning of User Profiles: Representational Issues. In Proceedings of the National Conference on Artificial Intelligence, 433–438.Google Scholar
  3. Brajnik, G. and Tasso, C. (1994). A Shell for Developing Non-monotonic User Modeling Systems. International Journal of Human-Computer Studies 40:31–62.CrossRefGoogle Scholar
  4. Chiu, P. (1997). Using C4.5 as an Induction Engine for Agent Modeling: An experiment of Optimisation. In Sixth User Modeling Conference, Workshop on Machine Learning for User Modeling.Google Scholar
  5. Fisher, D. H. (1987). Knowledge Acquisition via Incremental Conceptual Clustering. Machine Learning 2: 139–172.Google Scholar
  6. Gluck, M. A. and Corter, J. E. (1985). Information, Uncertainty and the Utility of Categories. In Proceedings of the 7th Conference of the Cognitive Science Society, 283–287.Google Scholar
  7. Kay, J. (1995). The urn Toolkit for Cooperative User Modeling. User Modeling and User Adapted Interaction 4:149–196.CrossRefGoogle Scholar
  8. Paliouras, G., Papatheodorou, C., Karkaletsis, V., Spyropoulos, C., and Malaveta, V. (1998). Learning User Communities for Improving the Services of Information Providers, Lecture Notes in Computer Science, 1513: Springer-Verlag. 367–384.CrossRefGoogle Scholar
  9. Quinlan, J. R. (1993). C4.5: Programs for Machine Learning, Kaufmann.Google Scholar
  10. Raskutti, B. and Beitz, A. (1996). Acquiring User Preferences for Information Filtering in Interactive Multi-Media Services. In Proceedings of PRICAI, 47–58.Google Scholar
  11. Rich, E. (1983). Users are Individuals: Individualizing User Models. International Journal of Man-Machine Studies 18:199–214.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 1999

Authors and Affiliations

  • Georgios Paliouras
    • 1
  • Vangelis Karkaletsis
    • 1
  • Christos Papatheodorou
    • 2
  • Constantine D. Spyropoulos
    • 1
  1. 1.Institute of Informatics and TelecommunicationsNational Centre for Scientific Research (NCSR) “Demokritos”Aghia Paraskevi AttikisGreece
  2. 2.Division of Applied TechnologiesNational Centre for Scientific Research (NCSR) “Demokritos”Aghia Paraskevi AttikisGreece

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