Project

We are pleased to announce that we have received a second NSF IIS grant for research on this event analytics vision.

NEW! Scalable Event Trend Analytics for Data Stream Inquiry, 2018

Data streams have grown in unprecedented scale and velocity in recent years. The real-time discovery of emerging event trends in data streams is essential for time-critical applications from computing infection spread patterns across major medical facilities to detecting frequent stock trends. Unfortunately, event trend analytics, i.e., the aggregation of complex event trends specified using Kleene-closure based patterns, is known to be not only of prohibitively high computational complexity but also to suffer from exorbitant memory utilization costs. This project overcomes the shortcomings of state-of-the-art systems by for the first time providing practical solutions for this important class of analytics.

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Complex Event Analytics, 2010

Recent advances in sensor technologies and expansion of wired and wireless communication protocols enable us to continuously collect information about the physical world, resulting in a rich set of novel services. The ability to infer relevant patterns from these event streams in real-time and at various levels of abstractions to make near instantaneous decisions is crucial for a wide range of mission critical applications ranging from real-time crisis management to security. This project designs, implements, and evaluates a novel complex event processing methodology, henceforth called Complex Event Analytics (CEA).

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