Mining Contextual Preference Rules for Building User Profiles

  • Sandra de Amo
  • Mouhamadou Saliou Diallo
  • Cheikh Talibouya Diop
  • Arnaud Giacometti
  • Haoyuan D. Li
  • Arnaud Soulet
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7448)


The emerging of ubiquitous computing technologies in recent years has given rise to a new field of research consisting in incorporating context-aware preference querying facilities in database systems. One important step in this setting is the Preference Elicitation task which consists in providing the user ways to inform his/her choice on pairs of objects with a minimal effort. In this paper we propose an automatic preference elicitation method based on mining techniques. The method consists in extracting a user profile from a set of user preference samples. In our setting, a profile is specified by a set of contextual preference rules verifying properties of soundness and conciseness. We evaluate the efficacy of the proposed method in a series of experiments executed on a real-world database of user preferences about movies.


Association Rule User Preference Preference Elicitation Minimal Support Threshold Preference Rule 
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 2012

Authors and Affiliations

  • Sandra de Amo
    • 1
  • Mouhamadou Saliou Diallo
    • 2
    • 3
  • Cheikh Talibouya Diop
    • 3
  • Arnaud Giacometti
    • 2
  • Haoyuan D. Li
    • 2
  • Arnaud Soulet
    • 2
  1. 1.Universidade Federal de UberlândiaBrazil
  2. 2.Université de ToursFrance
  3. 3.Université Gaston Berger de Saint-LouisSénégal

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