By relating observed and modelled behaviour, conformance checking unleashes the full
power of process mining. Techniques from this discipline enable the analysis of the quality …

PM4Py is a Python library providing a comprehensive array of tools for process mining. This
paper presents an in-depth overview of the PM4Py library, including its integration with other …

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 …

Gas explosion has always been one of the major accident types in the coal mines of China,
and reliable emergency rescue process is one of the key guarantees to minimize accident …

Virtually all techniques, developed in the area of process mining, assume the input event
data to be discrete, and, at a relatively high level (ie, close to the business-level). However …

While noting the importance of data quality, existing process mining methodologies (i) do not
provide details on how to assess the quality of event data (ii) do not consider how the …

Process discovery algorithms extract process models from business process event logs.
Existing discovery algorithms require upfront filtering, or specific parameter input, to produce …

Process workers may vary the normal execution of a business process to adjust to changes
in their operational environment, eg, changes in workload, season, or regulations. Changes …

Methods from the area of Process Mining traditionally focus on extracting insight in business
processes from event logs. In this paper we explore the potential of Process Mining to …

This paper presents 1) a novel hierarchy and recursion extension to the process tree model;
and 2) the first, recursion aware process model discovery technique that leverages …