Complex Event Recognition
Today's organisations collect data in various structured and unstructured digital formats, but they cannot fully utilise these data to support their resource management. It is evident that the analysis and interpretation of the collected data need to be automated, in order for large data volumes to be transformed into operational knowledge. Events are particularly important pieces of knowledge, as they represent activities of special significance within an organisation. Therefore, the recognition of events is of utmost importance. Consider, for example, the recognition of attacks on nodes of a computer network given the TCP/IP messages, the recognition of suspicious trader behaviour given the transactions in a financial market, and the recognition of whale songs given a symbolic representation of whale sounds. We invite quality submissions focusing on various aspects of event recognition, including analysis of video, audio, text and other sensor data, as well as recognition on fused data sources. While we place emphasis on theoretical contributions, we also welcome papers describing interesting applications.
Organizers: Grigoris Antoniou, University of Crete, Alexander Artikis, NCSR "Demokritos", Themis Palpanas, University of Trento, and Marek Sergot,, Imperial College London.
Topics:
- Representation languages for event recognition
- Algorithms for real-time event recognition
- Probabilistic reasoning for event recognition
- Machine learning for event recognition
- Event recognition architectures
- Benchmarks, performance evaluations, and testbeds
- Domain-specific deployments of event recognition systems
Program Committee:
- Darko Anicic, FZI, Germany
- Nick Bassiliades, Aristotle University, Greece
- Vangelis Karkaletsis, NCSR "Demokritos"
- Georgios Paliouras, NCSR "Demokritos"
- Jeremy Pitt, Imperial College London, UK
- Kostas Stathis, University of London, UK
