Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Logic and information
Ontology Based Context Modeling and Reasoning using OWL
PERCOMW '04 Proceedings of the Second IEEE Annual Conference on Pervasive Computing and Communications Workshops
Hybrid Context Model Based on Multilevel Situation Theory and Ontology for Contact Centers
PERCOMW '05 Proceedings of the Third IEEE International Conference on Pervasive Computing and Communications Workshops
A data-oriented survey of context models
ACM SIGMOD Record
Multisensor Data Fusion
IJCAI'93 Proceedings of the 13th international joint conference on Artifical intelligence - Volume 1
Context dynamic and explanation in contextual graphs
CONTEXT'03 Proceedings of the 4th international and interdisciplinary conference on Modeling and using context
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Successful management of critical situations created by major natural and man-made activities requires monitoring, recognizing, and making sense of these activities in order to support decision makers in either preventing a crisis or acting effectively to mitigate its adverse impact. Context plays an important role in crisis management since it provides decision makers with important information about current situations and situation dynamics in relation to their goals, functions and information needs, to enable them to appropriately adapt their decisions and actions. Efficient context exploitation for crises management requires a clear understanding of what context is and how to represent and use it. The paper represents an attempt to answer these questions by providing a discussion of the key issues of the problem of context definition, representation, discovery, and utilization in crisis management.