Background Knowledge of post-myocardial infarction (MI) disease risk to date is limited—yet
the number of survivors of MI has increased dramatically in recent decades. We investigated …

Process model comprehension is essential for a variety of technical and managerial tasks.
To facilitate comprehension, process models are often divided into subprocesses when they …

Process mining has significantly transformed business process management by introducing
innovative data-based analysis techniques and empowering organizations to unveil hidden …

Over the past few years, several software companies have emerged that offer process
mining tools to assist enterprises in gaining insights into their process executions. However …

Abstract Finite variant of Linear Temporal Logic (LTL f) is increasingly popular in Artificial
Intelligence (AI). Indeed, several AI applications rely on checking the satisfiability of temporal …

Modeling and analyzing collective adaptive systems with heterogeneous components poses
challenges to language designers, software engineers, and computer scientists interested in …

Many real-life processes naturally define partial orders over the activities they are composed
of. Partial orders can be used as a graph-like representation of process behavior, allowing …

Abstract Process mining and Robotic Process Automation (RPA) are two technologies of
great interest in research and practice. Process mining uses event logs as input, but much of …

Purpose The purpose of this study is to present a methodical procedure on how to prepare
event logs and analyse them through process mining, statistics and visualisations. The aim …

Machine learning models are routinely integrated into process mining pipelines to carry out
tasks like data transformation, noise reduction, anomaly detection, classification, and …