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Towards Context-Sensitive Intelligence

  • Holger Mügge
  • Tobias Rho
  • Marcel Winandy
  • Markus Won
  • Armin B. Cremers
  • Pascal Costanza
  • Roman Englert
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3527)

Abstract

Even modern component architectures do not provide for easily manageable context-sensitive adaptability, a key requirement for ambient intelligence. The reason is that components are too large – providing black boxes with adaptation points only at their boundaries – and to small – lacking good means for expressing concerns beyond the scope of single components – at the same time. We present a framework that makes components more fine-grained so that adaptation points inside of them become accessible, and more coarse-grained so that changes of single components result in the necessary update of structurally constrained dependants. This will lead to higher quality applications that fit better into personalized and context-aware usage scenarios.

Keywords

Speech Recognition Structural Constraint Variation Point Structure Schema Software Product Line 
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

  • Holger Mügge
    • 1
  • Tobias Rho
    • 1
  • Marcel Winandy
    • 1
  • Markus Won
    • 1
  • Armin B. Cremers
    • 1
  • Pascal Costanza
    • 2
  • Roman Englert
    • 3
  1. 1.Institute of Computer Science IIIUniversity of BonnBonnGermany
  2. 2.Programming Technology LabVrije Universiteit BrusselBrusselsBelgium
  3. 3.Deutsche Telekom LaboratoriesBerlinGermany

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