Issues and Requirements for Bayesian Approaches in Context Aware Systems

  • Michael Angermann
  • Patrick Robertson
  • Thomas Strang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3479)


Research in advanced context-aware systems has clearly shown a need to capture the inherent uncertainty in the physical world, especially in human behavior. Modelling approaches that employ the concept of probability, especially in combination with Bayesian methods, are promising candidates to solve the pending problems. This paper analyzes the requirements for such models in order to enable user-friendly, adaptive and especially scalable operation of context-aware systems. It is conjectured that a successful system may not only use Bayesian techniques to infer probabilities from known probability tables but learn, i.e. estimate the probabilities in these tables by observing user behavior.


Bayesian Network Bayesian Approach Domain Expert Pervasive Computing Dynamic Bayesian Network 
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 2005

Authors and Affiliations

  • Michael Angermann
    • 1
  • Patrick Robertson
    • 1
  • Thomas Strang
    • 1
  1. 1.Institute of Communications and NavigationGerman Aerospace CenterWessling/OberpfaffenhofenGermany

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