Matthias Weidlich

Query Decomposition for Efficient Pattern Matching

Queries for pattern matching characterize the joint occurrence of specific elements in sequential data. Their evaluation enables the detection of situations of interest, thereby providing a foundation for context-aware applications. While various models for pattern matching have been proposed, reaching from streaming languages in complex event processing to row pattern matching in SQL, they have in common that query evaluation is computational challenging. In this talk, we review recent results on generic decomposition schemes for pattern matching queries. They facilitate the distributed and parallel evaluation of pattern matching queries and, as such, provide an angle for their efficient evaluation.

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Biography

Matthias Weidlich is a full professor at the Department of Computer Science at Humboldt-Universität zu Berlin (HU Berlin), Germany, where he holds the Chair on Databases and Information Systems. Before joining HU Berlin, he held positions at Imperial College London and at the Technion - Israel Institute of Technology. He has a PhD in Computer Science from the Hasso-Plattner-Institute, University of Potsdam. His research focuses on data-driven process analysis, event stream processing, and exploratory data analysis. He serves as Co-Editor in Chief for the Information Systems journal and is a member of the steering committees of the ACM DEBS and BPM conference series.
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