Relational Dependency Networks
The Journal of Machine Learning Research
Ambient Intelligence—the Next Step for Artificial Intelligence
IEEE Intelligent Systems
A survey of context modelling and reasoning techniques
Pervasive and Mobile Computing
GeeAir: a universal multimodal remote control device for home appliances
Personal and Ubiquitous Computing
TaskShadow: Toward Seamless Task Migration across Smart Environments
IEEE Intelligent Systems
EventNet: inferring temporal relations between commonsense events
MICAI'05 Proceedings of the 4th Mexican international conference on Advances in Artificial Intelligence
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Smart environments require to percept conditions of people. Current context-aware systems mainly model limited user situations, which constrains their coverage and effect in real world usage. This paper proposes an encyclopedic knowledge network to enable practical context inference in our daily life by: 1) expressing essential semantics of contextual concepts and relations into a well-informed relational network, and 2) exploiting relational semantics to infer various contexts simultaneously. The performance of the approach is validated in real challenging problems and compared with inference of human being.