Learning Rules from User Behaviour

  • Domenico Corapi
  • Oliver Ray
  • Alessandra Russo
  • Arosha Bandara
  • Emil Lupu
Part of the IFIP International Federation for Information Processing book series (IFIPAICT, volume 296)


Pervasive computing requires infrastructures that adapt to changes in user behaviour while minimising user interactions. Policy-based approaches have been proposed as a means of providing adaptability but, at present, require policy goals and rules to be explicitly defined by users. This paper presents a novel, logic-based approach for automatically learning and updating models of users from their observed behaviour. We show how this task can be accomplished using a nonmonotonic learning system, and we illustrate how the approach can be exploited within a pervasive computing framework.


Logic Program Logic Programming Learn Rule Pervasive Computing Concept Drift 
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

© IFIP International Federation for Information Processing 2009

Authors and Affiliations

  • Domenico Corapi
    • 1
  • Oliver Ray
    • 2
  • Alessandra Russo
    • 1
  • Arosha Bandara
    • 3
  • Emil Lupu
    • 1
  1. 1.Imperial College LondonLondonUK
  2. 2.University of BristolBristolUK
  3. 3.The Open UniversityMilton KeynesUK

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