A Framework for Context Reasoning Systems

M. Przybilski, P. Nurmi, and P. Floréen (Finland)


Context Reasoning, Machine Learning, Software Architecture, Software Components


Finding a common structure for context reasoning systems is still rather difficult. Most context reasoning mechanisms are implemented in such a way that they support the spe cific study in mind. This paper first extends the understanding of context infor mation, based on the definition of Dey and Abowd, [1] and then introduces a structure for a context reasoning frame work. This framework takes into account the commonali ties amongst different inference and learning mechanisms and allows the re-use of those components. At the same time it allows the combination of different reasoning mech anisms, providing altogether a context reasoning engine that can be used for various context-aware applications.

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