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In pervasive computing environment the low-level context data provided by the sensors are usually meaningless, and thus higher-level context needs to be extracted. Situation is the semantic interpretation of low-level context, permitting a higher-level specification of human behavior in the scene and the corresponding system service. Context modeling and reasoning are the two key parts in the situation...
In pervasive computing environment the contexts are usually imprecise and incomplete due to unreliable connectivity, user mobility, and resource constraints. In this paper we present an approach based on the Dempster-Shafer Theory (DST) for the reasoning with imprecise context. To solve the two fundamental issues of the DST, computation intensiveness and the Zadeh paradox, we filer out excrescent...
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