Process mining provides a rich set of techniques to discover valuable knowledge of
business processes based on data that was recorded in different types of information …

A model is an artefact to represent a specific concept. It maps properties of the concept into
some abstract representation, driven by the purpose of the model. As such, models …

AI-augmented Business Process Management Systems (ABPMSs) are an emerging class of
process-aware information systems, empowered by trustworthy AI technology. An ABPMS …

Process mining techniques use event data to answer a variety of process-related questions.
Process discovery, conformance checking, model enhancement, and operational support …

Techniques to discover Petri nets from event data assume precisely one case identifier per
event. These case identifiers are used to correlate events, and the resulting discovered Petri …

Classical process mining relies on the notion of a unique case identifier, which is used to
partition event data into independent sequences of events. In this chapter, we study the …

Process event data is usually stored either in a sequential process event log or in a
relational database. While the sequential, single-dimensional nature of event logs aids …

Traditional approaches for process modeling and process analysis tend to focus on one type
of object (also referred to as cases or instances), and each event refers to precisely one …

Recent years have seen the emergence of object-centric process mining techniques. Born
as a response to the limitations of traditional process mining in analyzing event data from …

Process mining, as with any form of data analysis, relies heavily on the quality of input data
to generate accurate and reliable results. A fit-for-purpose event log nearly always requires …