Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Snoop: an expressive event specification language for active databases
Data & Knowledge Engineering
The Situation Manager Component of Amit - Active Middleware Technology
NGITS '02 Proceedings of the 5th International Workshop on Next Generation Information Technologies and Systems
Event Composition in Time-Dependent Distributed Systems
COOPIS '99 Proceedings of the Fourth IECIS International Conference on Cooperative Information Systems
Reasoning about Uncertainty
The VLDB Journal — The International Journal on Very Large Data Bases
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In recent years, there has been an increased need for the use of active systems – systems that include substantial processing which should be triggered by events. In many cases, however, there is an information gap between the actual occurrences of events to which such a system must respond, and the data generated by monitoring tools regarding these events. For example, some events, by their very nature, may not be signaled by any monitoring tools, or the inaccuracy of monitoring tools may incorrectly reflect the information associated with events. The result is that in many cases, there is uncertainty in the active system associated with event occurrence. In this paper, we provide a taxonomy of the sources of this uncertainty. Furthermore, we provide a formal way to represent this uncertainty, which is the first step towards addressing the aforementioned information gap.