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We present a system for online probabilistic event forecasting. We assume that a user is interested in detecting and forecasting event patterns, given in the form of regular expressions. Our system can consume streams of events and forecast when the pattern is expected to be fully matched. As more events are consumed, the system revises its forecasts to reflect possible changes in the state of the pattern. The framework of Pattern Markov Chains is used in order to learn a probabilistic model for the pattern, with which forecasts with guaranteed precision may be produced, in the form of intervals within which a full match is expected. Experimental results from real-world datasets are shown and the quality of the produced forecasts is explored, using both precision scores and two other metrics: spread, which refers to the “focusing resolution” of a forecast (interval length), and distance, which captures how early a forecast is reported.

Fri 23 Jun
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debs-2017-papers
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
Talk
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
Talk
Raef MousheimishDAVID lab, University of Versailles, Yehia TaherDAVID - UVSQ, Karine ZeitouniUniversity of Versailles-Saint-Quentin
debs-2017-papers11:20 - 11:40
Talk
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
Talk
Shima ZahmatkeshPolitecnico di Milano, Emanuele Della ValleDEIB, Politecnico di Milano, Daniele Dell'AglioIFI, University of Zurich