IJCNN 2020

Call for Papers

This special session, affiliated to the IEEE Task Force on Process Mining, is meant to offer a platform for sharing and publishing innovative research related to the problems of interpreting and analyzing complex event data (like those mentioned above), and of ultimately supporting the monitoring, analysis and improvement of the processes/systems that generated these data. The session is primarily interested in solution approaches relying on the discovery and refinement of behavioral models, or on the combination of high-level background knowledge with suitable data abstraction/interpretation techniques.

Papers addressing these problems from a methodological and computational perspective are welcome, as well as contributions presenting relevant applications. Researchers working in any of the related areas of Machine/Deep Learning, Process Mining, Complex Event Processing (CEP), Big Data Analytics and Business Process Management (BPM) are encouraged to submit contributions to this session.

The special session’s topics include, but are not limited to:

• Event log abstraction/interpretation
• Extracting behavioral or process-oriented models from low-level and/or incomplete logs (possibly mixing up structured and unstructured data)
• Learning Deep Neural models for making predictions and recommendations on the basis of low-level and/or incomplete log data
• Conformance checking and deviance detection on low-level uncertain log data
• Activity recognition and anomaly detection on low-level log data
• Semantics-aware Complex Event Processing
• Human-in-the-loop machine/deep learning frameworks for the analysis of event logs (e.g., combining learning and reasoning modules, featuring explanation mechanisms, and taking feedback/guidance from the analyst/user in the form of constraints/preferences)
• Hybrid event-analysis or process-optimization methods combining symbolic and statistical methods
• Benchmarks and comparative empirical analysis of existing solutions on public data
• Application to real-life settings: BPM systems, IoT systems, Industrial logs, Social Networking systems, Smart Homes/Buildings/Cities, Healthcare systems, etc.

All papers accepted and presented at the IEEE IJCNN 2020 will be included in the conference proceedings published by IEEE Explore. A selection of the accepted papers will be considered for publication on a special issue of a SCOPUS indexed journal (to be announced).