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Erschienen in:
2012 | OriginalPaper | Buchkapitel
Automatic Description of Context-Altering Services through Observational Learning
verfasst von : Katharina Rasch, Fei Li, Sanjin Sehic, Rassul Ayani, Schahram Dustdar
Erschienen in: Pervasive Computing
Verlag: Springer Berlin Heidelberg
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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.