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Leveraging the regularities of people's trajectories, mobility prediction can help forecast social interaction opportunities. In this paper, in order to facilitate real-world social interaction, we aim to predict “serendipitous” social interactions, which are defined as unplanned encounters and interaction opportunities and regarded as emerging social interactions. We collected GPS trajectory data...
Applications in context-aware computing continuously change their operations based on sensor data or services provided by various physical spaces in the real world, such as persons, shops and homes. We propose a gateway framework for physical spaces in this paper, which serves as a middleware platform for context-aware applications to access data from sensor networks deployed in these spaces. The...
In this paper, we propose a peer-to-peer approach to derive and obtain additional context data from low-level context data that may be spread over multiple domains in pervasive computing environments. In this system, peers are self-organized into a semantic peer- to-peer network as the underlying communication substrate. Context reasoning is done in a distributed fashion through logical reasoning...
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