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 semantic 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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Sorici, A., Boissier, O., Picard, G., Zimmermann, A. (2013). Applying Semantic Web Technologies to Context Modeling in Ambient Intelligence. In: O’Grady, M.J., et al. Evolving Ambient Intelligence. AmI 2013. Communications in Computer and Information Science, vol 413. Springer, Cham. https://doi.org/10.1007/978-3-319-04406-4_22
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DOI: https://doi.org/10.1007/978-3-319-04406-4_22
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-04405-7
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