Write a Blog >>

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

10:30 - 12:10: DEBS Research Papers - Session 5: Learning, Automation and Integration at Sala d'Actes, Vertex Building
Chair(s): Martin HirzelIBM Research
debs-2017-papers10:30 - 10:55
Elias AlevizosNCSR Demokritos, Institute of Informatics and Telecommunications, Alexander ArtikisUniversity of Pireaus and NCSR "Demokritos", Georgios PaliourasInstitute of Informatics & Telecommunications, NCSR "Demokritos"
debs-2017-papers10:55 - 11:20
Raef MousheimishDAVID lab, University of Versailles, Yehia TaherDAVID - UVSQ, Karine ZeitouniUniversity of Versailles-Saint-Quentin
debs-2017-papers11:20 - 11:40
Jürgen Thanhofer-PilischChristian Doppler Lab. MEVSS, Johannes Kepler University Linz, Rick RabiserChristian Doppler Lab. MEVSS, Johannes Kepler University Linz, Thomas KrismayerChristian Doppler Lab. MEVSS, Johannes Kepler University Linz, Michael VierhauserUniversity of Notre Dame, Paul Grünbacher, Stefan WallnerPrimetals Technologies Austria GmbH, Klaus SeyerlehnerPrimetals Technologies Austria GmbH, Helmut ZeiselPrimetals Technologies Austria GmbH
debs-2017-papers11:40 - 12:00
Shima ZahmatkeshPolitecnico di Milano, Emanuele Della ValleDEIB, Politecnico di Milano, Daniele Dell'AglioIFI, University of Zurich