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

Process mining allows analysts to exploit logs of historical executions of business processes
to extract insights regarding the actual performance of these processes. One of the most …

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 …

Educational process mining (EPM) is an emerging field in educational data mining (EDM)
aiming to make unexpressed knowledge explicit and to facilitate better understanding of the …

We present a systematic literature review of data-driven self-regulated learning (SRL) that
emphasises the methodological importance of temporality and sequence, as opposed to …

Process discovery is the problem of, given a log of observed behaviour, finding a process
model that 'best'describes this behaviour. A large variety of process discovery algorithms …

Given an event log describing observed behaviour, process discovery aims to find a process
model that 'best'describes this behaviour. A large variety of process discovery algorithms …

The audit of financial statements is a complex and highly specialized process. Digitalization
and the increasing automation of transaction processing create new challenges for auditors …

Performing business process analysis in healthcare organizations is particularly difficult due
to the highly dynamic, complex, ad hoc, and multi-disciplinary nature of healthcare …

One of the aims of process mining is to retrieve a process model from a given event log.
However, current techniques have problems when mining processes that contain nontrivial …