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Event Processing Under Uncertainty

By Er Artikis, Opher Etzion, Zohar Feldman and Fabiana Fournier

Abstract

Big data is recognized as one of the three technology trends at the leading edge a CEO cannot afford to overlook in 2012. Big data is characterized by volume, velocity, variety and veracity (“data in doubt”). As big data applications, many of the emerging event processing applications must process events that arrive from sources such as sensors and social media, which have inherent uncertainties associated with them. Consider, for example, the possibility of incomplete data streams and streams including inaccurate data. In this tutorial we classify the different types of uncertainty found in event processing applications and discuss the implications on event representation and reasoning. An area of research in which uncertainty has been studied is Artificial Intelligence. We discuss, therefore, the main Artificial Intelligence-based event processing systems that support probabilistic reasoning. The presented approaches are illustrated using an example concerning crime detection

Topics: Event Recognition, Pattern Matching, Uncertainty, Artificial Intelligence
Year: 2014
OAI identifier: oai:CiteSeerX.psu:10.1.1.418.3695
Provided by: CiteSeerX
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