Abstract
One important functionality provided by a context-aware infrastructure is to derive high-level contexts on behalf of context-aware applications. High-level contexts are summary descriptions about users’ states and surroundings which are generally inferred from low-level, explicit contexts directly provided by hardware sensors and software programs. In Semantic Space, an ontology-based context-aware infrastructure, high-level contexts are derived using context reasoning. In this paper, we present another approach to deriving high-level contexts in Semantic Space, event-driven context interpretation. We show how event-driven context interpretation can leverage on the context model and dynamic context acquisition/representation in Semantic Space as well as easily integrate into Semantic Space. Differing from the context reasoning approach, our proposed event-driven context interpreter offers better performance in terms of flexibility, scalability and processing time. We also present a prototype of the event-driven context interpreter we are building within Semantic Space to validate the feasibility of the new approach.
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Tan, J.G., Zhang, D., Wang, X., Cheng, H.S. (2005). Enhancing Semantic Spaces with Event-Driven Context Interpretation. In: Gellersen, H.W., Want, R., Schmidt, A. (eds) Pervasive Computing. Pervasive 2005. Lecture Notes in Computer Science, vol 3468. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11428572_6
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DOI: https://doi.org/10.1007/11428572_6
Publisher Name: Springer, Berlin, Heidelberg
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