Process mining (PM) is a well‐known research area that includes techniques,
methodologies, and tools for analyzing processes in a variety of application domains. In the …

Within the research domain of process mining, process discovery aims at constructing a
process model as an abstract representation of an event log. The goal is to build a model …

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 …

Process mining allows for the automated discovery of process models from event logs.
These models provide insights and enable various types of model-based analysis. This …

Many software engineering activities process the events contained in log files. However,
before performing any processing activity, it is necessary to parse the entries in a log file, to …

Process mining includes the automated discovery of processes from event logs. Based on
observed events (eg, activities being executed or messages being exchanged) a process …

The practical relevance of process mining is increasing as more and more event data
become available. Process mining techniques aim to discover, monitor and improve real …

Considerable amounts of data, including process events, are collected and stored by
organisations nowadays. Discovering a process model from such event data and verification …

Process Conformance is a crucial step in the area of Process Mining: the adequacy of a
model derived from applying a discovery algorithm to a log must be certified before making …

As organizations change, their information systems can evolve from simple systems to
complex systems, which are hard to understand, and therefore hard to maintain or extend …