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 is a growing and promising study area focused on understanding processes
and to help capture the more significant findings during real execution rather than, those …

With the focus of smart construction project management, this paper presents a closed-loop
digital twin framework under the integration of Building Information Modeling (BIM), Internet …

Adoption of digital twins in smart factories, that model real statuses of manufacturing systems
through simulation with real time actualization, are manifested in the form of increased …

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 …

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 …

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 …

The problem of automated discovery of process models from event logs has been
intensively researched in the past two decades. Despite a rich field of proposals, state-of-the …