Applying semantic web technologies to context modeling in ambient intelligence

Abstract : Representation and reasoning about context information is a main area of research in Ambient Intelligence (AmI). Given the openness and decentralization of many AmI applications, we argue that usage of se- mantic web technologies for context modeling brings advantages in terms of standards, uniform representation and expressive reasoning. We present an approach for modeling of context information which builds and improves upon related lines of work (SOUPA, CML, annotated RDF). We provide a formalization of the model and an innovative realization using the latest proposals for semantic web standards like RDF and SPARQL. A commonly encountered ambient intelligence scenario showcases the approach.
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Communication dans un congrès
3rd International Workshop on Pervasive and Context-Aware Middleware (PerCAM 2013) in conjunction with Fourth International Joint Conference on Ambient Intelligence (AmI 2013), Dec 2013, Dublin, Ireland. Volume 413, pp 217-229, 2013, 〈10.1007/978-3-319-04406-4_22〉
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https://hal-emse.ccsd.cnrs.fr/emse-00868038
Contributeur : Florent Breuil <>
Soumis le : mardi 1 octobre 2013 - 09:33:16
Dernière modification le : jeudi 5 mars 2015 - 01:01:13

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Alexandru Sorici, Olivier Boissier, Gauthier Picard, Antoine Zimmermann. Applying semantic web technologies to context modeling in ambient intelligence. 3rd International Workshop on Pervasive and Context-Aware Middleware (PerCAM 2013) in conjunction with Fourth International Joint Conference on Ambient Intelligence (AmI 2013), Dec 2013, Dublin, Ireland. Volume 413, pp 217-229, 2013, 〈10.1007/978-3-319-04406-4_22〉. 〈emse-00868038〉

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