Ontology Based Context Modeling and Reasoning using OWL
PERCOMW '04 Proceedings of the Second IEEE Annual Conference on Pervasive Computing and Communications Workshops
An ontology for context-aware pervasive computing environments
The Knowledge Engineering Review
Applying a Disciplined Approach to the Development of a Context-Aware Communication Application
PERCOM '05 Proceedings of the Third IEEE International Conference on Pervasive Computing and Communications
Situations in Conceptual Modeling of Context
EDOCW '06 Proceedings of the 10th IEEE on International Enterprise Distributed Object Computing Conference Workshops
A Rule-Based Approach Towards Context-Aware User Notification Services
PERSER '06 Proceedings of the 2006 ACS/IEEE International Conference on Pervasive Services
Jess in action: rule-based systems in java
Jess in action: rule-based systems in java
Human-Computer Interaction
Developing context-aware pervasive computing applications: Models and approach
Pervasive and Mobile Computing
Model-driven development of context-aware services
DAIS'06 Proceedings of the 6th IFIP WG 6.1 international conference on Distributed Applications and Interoperable Systems
Combining ontologies and scenarios for context-aware e-learning environments
Proceedings of the 28th ACM International Conference on Design of Communication
Situation recognition: an evolving problem for heterogeneous dynamic big multimedia data
Proceedings of the 20th ACM international conference on Multimedia
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Context-aware applications use and manipulate context information to detect high-level situations, which are used to adapt application behavior. This paper discusses the specification of situations in context-aware applications and introduces a rule-based approach to detect situations. Situations are specified using a combination of UML class diagrams and OCL constraints. We support a wide range of situations, which can be composed of more elementary kinds of context. We discuss how to cope with distribution and to exploit it beneficially for context manipulation and situation detection. We employ a generic rule-based platform (DJess [2]) to support the derivation of situations in a distributed fashion.