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Active service is one of key problems of ubiquitous computing paradigm. Context‐aware computing is helpful to carry out this service. Because the context is changing with the movement or shift of the user, its uncertainty often exists. Context‐aware computing with uncertainty includes obtaining context information, forming model, fusing of aware context and managing context information. In this paper, we focus on modeling and computing of aware context information with uncertainty for making dynamic decision during seamless mobility. Our insight is to combine dynamic context‐aware computing with improved Random Set Theory (RST) and extended D‐S Evidence Theory (EDS). We re‐examine formalism of random set, argue the limitations of the direct numerical approaches, give new modeling mode based on RST for aware context and propose our computing approach of modeled aware context.In addition, we extend classic D‐S Evidence Theory after considering context’s reliability, time‐efficiency and relativity, compare relative computing methods. After enumerating experimental examples of our active space, we provide the evaluation. By comparisons, the validity of new context‐aware computing approach based on RST or EDS for ubiquitous active service with uncertainty information has been successfully tested.

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