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Ontology Based Context Modeling and Reasoning using OWL
PERCOMW '04 Proceedings of the Second IEEE Annual Conference on Pervasive Computing and Communications Workshops
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IEEE Transactions on Knowledge and Data Engineering
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IEEE Transactions on Knowledge and Data Engineering
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IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
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IEEE Transactions on Consumer Electronics
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The incapability to foresee or react to all the events that take place in a specific environment supposes an important handicap for Ambient Intelligence systems, expected to be self-managed, proactive, and goal-driven. Endowing such systems with capabilities to understand and reason about context seems like a promising solution to overcome this hitch. Supported on the service-oriented paradigm, composing rather than combining services provides a reasonable mean to implement versatile systems. This paper describes how systems for Ambient Intelligence can be improved by combining automatic service composition and reasoning capabilities upon a distributed middleware framework.