Purpose The purpose of this paper is to review empirical studies on process mining in order
to understand its use by organizations. The paper further aims to outline future research …

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 …

Big data are a commonly discussed topic, and their value in marketing and sales has been
thoroughly investigated. Although some authors have also discussed their relevance to …

The integration of the huge data streams produced by the Industrial Internet of Things (IIoT)
can provide invaluable knowledge in the context of Industry 4.0, and is also an open …

Detecting anomalies is important for identifying inefficiencies, errors, or fraud in business
processes. Traditional process mining approaches focus on analyzing 'flattened', sequential …

Process pattern discovery methods (PPDMs) aim at identifying patterns of interest to users.
Existing PPDMs typically are unsupervised and focus on a single dimension of interest, such …

Business processes represent a cornerstone to the operation of any enterprise. They are the
operational means for such organizations to fulfill their goals. Nowadays, enterprises are …

The plethora of algorithms in the research field of process mining builds on directly-follows
relations. Even though various improvements have been made in the last decade, there are …

Process models generated through process mining depict the as-is state of a process.
Through annotations with metrics such as the frequency or duration of activities, these …

Conformance checking allows organizations to compare process executions recorded by
the IT system against a process model representing the normative behavior. Most of the …