The field of process mining focuses on distilling knowledge of the (historical) execution of a
process based on the operational event data generated and stored during its execution …

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 …

The strong impulse to digitize processes and operations in companies and enterprises have
resulted in the creation and automatic recording of an increasingly large amount of process …

Rapidly changing business environments expose companies to high levels of uncertainty.
This uncertainty manifests itself in significant changes that tend to occur over the lifetime of a …

The focus of this paper is on how data quality can affect business process discovery in real
complex environments, which is a major factor determining the success in any data-driven …

Developments in machine learning together with the increasing usage of sensor data
challenge the reliance on deterministic logs, requiring new process mining solutions for …

We propose an approach to identify anomalies in business processes by building an
anomaly detector using graph encodings of process event log data coupled with graph …

With the growing number of devices, sensors and digital systems, data logs may become
uncertain due to, eg, sensor reading inaccuracies or incorrect interpretation of readings by …

With Process discovery algorithms, we discover process models based on event data,
captured during the execution of business processes. The process discovery algorithms …

One major result of the Industrial Digitalization is the access to a large set of digitalized data
and information, ie Big Data. The market of analytic tools offers a huge variety of algorithms …