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 …

The goal of process discovery is to visualize event log data as a process model. In reality,
however, these models are often highly complex. Process trace clustering is a well-studied …

This thesis is about process mining: the analysis an organization's processes by using
process execution data. During the handling of a case or process instance data about the …

In this paper we describe a method to discover frequent behavioral patterns in event logs.
We express these patterns as local process models. Local process model mining can be …

Process mining techniques analyze processes based on events stored in event logs. Yet,
low-level events recorded by information systems may not directly match high-level activities …

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 …

Robotic Process Automation (RPA) is a novel approach for immediate cost reduction and
gaining operational efficiency. RPA tools can automate repeatable tasks, thus reducing the …

Human behavior could be represented in the form of a process. Existing process modeling
notations, however, are not able to faithfully represent these very flexible and unstructured …

Process mining has shown that it provides valuable insights in terms of uncovering
bottlenecks and inefficiencies in processes or identifying tasks for automation. However …

Process mining techniques are used to extract knowledge about the efficiency and
compliance of an organization's business processes through process models. Real-life …