Integrating Multilingual Text Classification Tasks and User Modeling in Personalized Newspaper Services

  • Alberto Díaz Esteban
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2109)


In this paper a methodology designed to improve the intelligent personalization of newspaper services is presented. The methodology integrates textual content analysis tasks to achieve an elaborate user model, which represents separately short-term needs and long-term multi-topic interests. The characterization of user’s interests includes his preferences about structure, content and information delivery. A wide coverage and non-specific-domain classification of topics and a personal set of keywords allow the user to define his preferences about content. The application of implicit feedback allows a proper and dynamic personalization. Another topic that have been addressed in the thesis is the evaluation of systems offering to send users a selection of the daily news by electronic mail. Finally, the extensions to a multilingual framework are studied.


Short/long-term models multi-topic user profile adaptive user model evaluation multilingual text classification tasks 


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  1. 1.
    Amato, G., Straccia, U.: User Profile Modeling and Applications to Digital Libraries. In: Abiteboul, S., Vercoustre, A.M. (eds.), Proceedings of the Third European Conference on Research and Advanced Technology for Digital Libraries, Lecture Notes in Computer Science 1696 (1999) 184–197, Springer-VerlagCrossRefGoogle Scholar
  2. 2.
    Billsus, D., Pazzani, M.J.: A Hybrid User Model for News Story Classification. In: Proceedings of the Seventh International Conference on User Modeling, Banff, Canada (1999)Google Scholar
  3. 3.
    Chen, L., Sycara, K.P.: WebMate: A Personal Agent for Browsing and Searching. In: Proceedings of the Second International Conference on Autonomous Agents, Minneapolis, (1998)Google Scholar
  4. 4.
    Díaz, A., Gervás, P., García, A.: Evaluating a User-Model Based Personalisation Architecture for Digital News Services. In: Proceedings of the Fourth European Conference on Research and Advanced Technology for Digital Libraries, Lisbon, Portugal (2000).Google Scholar
  5. 5.
    Díaz, A., Gervás, P., García, A., Chacón, I.: Sections, categories and keywords as interest specification tools for personalised news services. Online Information Review, OIR 2001, no 3. (in press)Google Scholar
  6. 6.
    Salton, G., McGill, M.J.: Introduction to Modern Information Retrieval. McGraw Hill, New York (1983)zbMATHGoogle Scholar
  7. 7.
    Sebastiani, F. (1999) A Tutorial on Automated Text Categorisation. In Proceedings of the First Argentinean Symposium on Artificial Intelligence (ASAI-99).Google Scholar
  8. 8.
    Yan, T.W., Garcia-Molina, H.: SIFT-A Tool for Wide-Area Information Dissemination. In: Proceedings of the USENIX Technical Conference, (1995)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Alberto Díaz Esteban
    • 1
  1. 1.Departamento de Inteligencia ArtificialUniversidad EuropeaMadridSpain

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