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• W2597157783 abstract "In a world of increasing dynamism, context-awareness gives promise through the ability to detect changes in the context of devices, environment, and people. Equally, with stream reasoning using languages including C-SPARQL, continuous streams of raw data in RDF can be reasoned over for context-awareness. Writing many context queries and rules this way can however be error prone, and often contains boilerplate. In this paper, we present a context modelling notation designed to support the creation of context-awareness based on stream reasoning systems. In validating our language there is tool support which, amongst other benefits, can generate context queries in C-SPARQL and context aggregation rules for higher level context knowledge processing. An Android-compatible mobile platform context reasoner was developed which can handle these deployable context rules. This methodology and associated tools has been validated as part of an EU funded project." @default.
• W2597157783 created "2017-03-23" @default.
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• W2597157783 date "2017-01-01" @default.
• W2597157783 modified "2023-09-27" @default.
• W2597157783 title "Supporting Context-Aware Engineering Based on Stream Reasoning" @default.
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• W2597157783 doi "https://doi.org/10.1007/978-3-319-57837-8_37" @default.
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