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Automatic Description of Context-Altering Services through Observational Learning

  • Katharina Rasch
  • Fei Li
  • Sanjin Sehic
  • Rassul Ayani
  • Schahram Dustdar
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7319)

Abstract

Understanding the effect of pervasive services on user context is critical to many context-aware applications. Detailed descriptions of context-altering services are necessary, and manually adapting them to the local environment is a tedious and error-prone process. We present a method for automatically providing service descriptions by observing and learning from the behavior of a service with respect to its environment. By applying machine learning techniques on the observed behavior, our algorithms produce high quality localized service descriptions. In a series of experiments we show that our approach, which can be easily plugged into existing architectures, facilitates context-awareness without the need for manually added service descriptions.

Keywords

Smart Home Context Change Service Description Capability Learning Service Execution 
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

  • Katharina Rasch
    • 1
  • Fei Li
    • 2
  • Sanjin Sehic
    • 2
  • Rassul Ayani
    • 1
  • Schahram Dustdar
    • 2
  1. 1.School of Information and Communication TechnologyKTH Royal Institute of TechnologyStockholmSweden
  2. 2.Distributed Systems GroupVienna University of TechnologyWienAustria

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