The Pyramid Collaborative Filtering Method: Toward an Efficient E-Course

  • Sofiane A. Kiared
  • Mohammed A. Razek
  • Claude Frasson
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4053)


Web-based applications with very diverse learners fail because they fail to satisfy various needs. Some people use collaborative filtering methods to analyze learners’ profiles and provide recommendation to a new learners, but this methods provides false recommendations from beginners. We present a new method, which provides recommendations that depend on the credibility rather than the number of learners. We have designed, implemented, and tested what we call the Intelligent E-Course Agent (IECA). Our evaluation experiment shows that our approach greatly improves learners’ knowledge and therefore presents a course that is more closely related to their needs.


Recommender System Collaborative Filter Intelligent Tutor System Computer Support Cooperative Work Dominant Meaning 
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 2006

Authors and Affiliations

  • Sofiane A. Kiared
    • 1
  • Mohammed A. Razek
    • 2
  • Claude Frasson
    • 1
  1. 1.Département d’informatique et de recherche opérationnelleUniversité de MontréalMontréalCanada
  2. 2.Faculty of Science, Math. and Computer Science DepartmentAzhar UniversityCairoEgypt

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