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Complex Event Recognition Group

National Center for Scientific Research Demokritos
We are Hiring
BSc & MSc Topics

Latest News

Our paper “A Framework to Evaluate Early Time-Series Classification Algorithms” was accepted at EDBT 2024. PDF code
We gave a tutorial on Proactive Streaming Analytics at CIKM 2023. Paper Slides
Our paper entitled “Online Semi-Supervised Learning of Composite Event Rules by Combining Structure and Mass-Based Predicate Similarity” has been accepted at the Machine Learning Journal. PDF DOI
The program and the proceedings of TIME 2023 are now available!
Our paper entitled “Online Event Recognition over Noisy Data Streams” has been accepted at the International Journal of Approximate Reasoning. PDF BibTeX code DOI

About the CER Group


We have been developing formal computational methods which take as input streams of low-level events, e.g. sensor-based events, such as a change in temperature, and combine them to infer complex high-level events of interest, such as the start of a fire incident or a fault in the cooling system of a vehicle. Our methods support real-time event recognition over high-velocity data streams, online structure learning for accurate event recognition over noisy relational streams, as well as complex event forecasting for proactive decision-making. Below are some applications in which we have applied our methods. An overview of our research activities may be found in this paper and this presentation.

Transport
Mobility
Analyze vehicle position streams for real-time fleet management.