Many algorithms now exist for discovering process models from event logs. These models
usually describe a control flow and are intended for use by people in analysing and …

Stochastic process models are a type of model that explicitly include elements of probability
in describing an organization, facilitating different modes of analysis and simulation. Having …

The prospect of data misuse negatively affecting our life has lead to the concept of
responsible data science. It advocates for responsibility to be built, by design, into data …

Machine learning models are routinely integrated into process mining pipelines to carry out
tasks like data transformation, noise reduction, anomaly detection, classification, and …

Process models describe the desired or observed behaviour of organisations. In stochastic
process mining, computational analysis of trace data yields process models which describe …

This paper presents a command-line tool, called Entropia, that implements a family of
conformance checking measures for process mining founded on the notion of entropy from …

Machine learning models are routinely integrated into process mining pipelines to carry out
tasks like data transformation, noise reduction, anomaly detection, classification, and …

A process is a collection of actions that were already, are currently being, or must be taken in
order to achieve a goal, where an action is an atomic unit of work, for instance, a business …

Event logs have become a valuable information source for business process management,
eg, when analysts discover process models to inspect the process behavior and to infer …

This research investigates how organisations behave by analysing the data they produce.
Discovering the hidden structure of organisational processes is a step towards …