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Event Prediction

  • Reference work entry
Encyclopedia of Database Systems

Synonyms

Prediction regarding future events; Prediction of event occurrence

Definition

Event prediction is the capability to estimate the possibility that some event may occur in the future. Some applications may even be required to advance beyond simply predicting the occurrence of events and need to influence the occurrence of some future event. For example, this may involve either decreasing the chance that a non-desirable event will occur or increasing the chance that a desirable event will occur. To determine whether or not such actions should indeed be carried out requires decision-making capabilities.

Historical Background

The first event-based systems were active databases in which automatic actions were carried out as a result of database queries. This was done using the ECA(Event-Condition-Action) paradigm. As such applications evolved, the events to which applications were required to respond evolved beyond single queries (e.g., insertion of deletions of data) and needed...

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Recommended Reading

  1. Alpaydin E. Introduction to Machine Learning. MIT Press, Cambridge, MA, 2004.

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  2. Brockwell P.J. and Davis R.A. Introduction to Time Series and Forecasting. Springer, New York, 2002.

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  3. Fishburn P.C. The Foundations of Expected Utility. Kluwer, Dordrecht, 1982.

    MATH  Google Scholar 

  4. Halpern J.Y. Reasoning about Uncertainty. MIT Press, Cambridge, MA, 2003.

    MATH  Google Scholar 

  5. Luckham D. The Power of Events: An Introduction to Complex Event Processing in Distributed Enterprise Systems. Addison-Wesley, Reading, MA, 2002.

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  6. Wasserkrug S., Gal A., and Etzion O. A model for reasoning with uncertain rules in event composition systems. In Proc. 21st Annual Conf. on Uncertainty in Artificial Intelligence, 2005, pp. 599–608.

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© 2009 Springer Science+Business Media, LLC

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Wasserkrug, S. (2009). Event Prediction. In: LIU, L., ÖZSU, M.T. (eds) Encyclopedia of Database Systems. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-39940-9_581

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