Process Mining focuses on extracting knowledge from data generated and stored in
corporate information systems in order to analyze executed processes. In the healthcare …

Concept drift in process mining (PM) is a challenge as classical methods assume processes
are in a steady-state, ie, events share the same process version. We conducted a systematic …

Engineering of knowledge-intensive processes (KiPs) is far from being mastered, since they
are genuinely knowledge-and data-centric, and require substantial flexibility, at both design …

Business process management has been the driving force of optimization and operational
efficiency for companies until now, but the digitalization era we have been experiencing …

Process mining is the research domain that is dedicated to the a posteriori analysis of
business process executions. The techniques developed within this research area are …

In semi-structured case-oriented business processes, the sequence of process steps is
determined by case workers based on available document content associated with a case …

Predicting next events in predictive process monitoring enables companies to manage and
control processes at an early stage and reduce their action distance. In recent years …

Process discovery, one of the key challenges in process mining, aims at discovering process
models from process execution data stored in event logs. Most discovery algorithms assume …

Artful processes are those processes in which the experience, intuition, and knowledge of
the actors are the key factors in determining the decision making. They are typically carried …

Process mining researchers have primarily focused on developing and improving process
discovery techniques, while attention for the applicability of process mining has been below …