Incremental Process Discovery

This book constitutes the revised version of the award-winning PhD dissertation written by the author at RWTH Aachen, Germany.

It presents a framework for incremental process discovery that allows users to learn and refine process models from event data iteratively. Next to process discovery and event data handling, it also contributes to conformance checking, a further fundamental process mining task. Eventually, it presents Cortado, an open-source process mining software tool that implements the algorithms and techniques proposed in an integrated and comprehensive fashion. This part also includes a case study applying Cortado and, therefore, the various contributions of this thesis in a real-life scenario.

In 2024, this PhD dissertation won the Best Process Mining PhD Dissertation Award by the IEEE Task Force for Process Mining, granted to outstanding PhD theses in this field.

Won the 2024 Best Process Mining PhD Dissertation Award by the IEEE Task Force for Process Mining Presents a framework for incremental process discovery enabling users to learn & refine process models from event data Introduces Cortado, an open-source process mining tool that implements the presented algorithms and techniques

Inhalt

Opening and fundamentals.- incremental process discovery.- facilitating interaction with event data.- realization and application.- closure.