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Due to the undeniable advantage of prediction and proactivity, many research areas and industrial applications are accelerating the pace to keep up with data science and predictive analytics. However and due to three well-known facts, the reactive Complex Event Processing (CEP) technology might lag behind when prediction becomes a requirement. 1st fact: The one and only inference mechanism in this domain is totally guided by CEP rules. 2nd fact: The only way to define a CEP rule is by writing it manually with the help of a human expert. 3r d fact: Experts tend to write reactive CEP rules, because and regardless of the level of expertise, it is nearly impossible to manually write predictive CEP rules. Combining these facts together, the CEP is—and will stay— a reactive computing technique. Therefore in this article, we present a novel data mining-based approach that automatically learns predictive CEP rules. The approach proposes a new learning algorithm where complex patterns from multivariate time series are learned. Then at run-time, a seamless transformation into the CEP world takes place. The result is a ready-to-use CEP engine with enrolled predictive CEP rules. Many experiments on publicly-available data sets demonstrate the effectiveness of our approach.

Fri 23 Jun

Displayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change

10:30 - 12:10
Session 5: Learning, Automation and IntegrationDEBS Research Papers at Sala d'Actes, Vertex Building
Chair(s): Martin Hirzel IBM Research
10:30
25m
Talk
Event Forecasting with Pattern Markov Chains. (Research Paper)
DEBS Research Papers
Elias Alevizos NCSR Demokritos, Institute of Informatics and Telecommunications, Alexander Artikis University of Pireaus and NCSR "Demokritos", Georgios Paliouras Institute of Informatics & Telecommunications, NCSR "Demokritos"
10:55
25m
Talk
Automatic Learning of Predictive CEP Rules: Bridging the Gap between Data Mining and Complex Event Processing. (Research Paper)
DEBS Research Papers
Raef Mousheimish DAVID lab, University of Versailles, Yehia Taher DAVID - UVSQ, Karine Zeitouni University of Versailles-Saint-Quentin
11:20
20m
Talk
An Event-based Capture-and-Compare Approach to Support the Evolution of Systems of Systems. (Experience Paper)
DEBS Research Papers
Jürgen Thanhofer-Pilisch Christian Doppler Lab. MEVSS, Johannes Kepler University Linz, Rick Rabiser Christian Doppler Lab. MEVSS, Johannes Kepler University Linz, Thomas Krismayer Christian Doppler Lab. MEVSS, Johannes Kepler University Linz, Michael Vierhauser University of Notre Dame, Paul Grünbacher , Stefan Wallner Primetals Technologies Austria GmbH, Klaus Seyerlehner Primetals Technologies Austria GmbH, Helmut Zeisel Primetals Technologies Austria GmbH
11:40
20m
Talk
Using Rank Aggregation in Continuously Answering SPARQL Queries on Streaming and Quasi-static Linked Data. (Experience Paper)
DEBS Research Papers
Shima Zahmatkesh Politecnico di Milano, Emanuele Della Valle DEIB, Politecnico di Milano, Daniele Dell'Aglio IFI, University of Zurich