Rapidly changing business environments expose companies to high levels of uncertainty.
This uncertainty manifests itself in significant changes that tend to occur over the lifetime of a …

We propose an approach to identify anomalies in business processes by building an
anomaly detector using graph encodings of process event log data coupled with graph …

Process Mining consists of techniques where logs created by operative systems are
transformed into process models. In process mining tools it is often desired to be able to …

In predictive process analytics, current and historical process data in event logs is used to
predict the future, eg, to predict the next activity or how long a process will still require to …

Business processes in workflows comprise of an ordered sequence of tasks and decisions
to accomplish certain business goals. Each decision point requires the input of a decision …

Approaches have been proposed in process mining to predict the completion time of
process instances. However, the accuracy levels of the prediction models depend on how …

A common challenge for improving business processes in large organizations is that
business people in charge of the operations are lacking a fact-based understanding of the …

Few approaches allow assertive estimates for ticket completion time in incident
management. The accuracy level of prediction models depends on how useful the used …

Process mining has emerged as a new scientific research topic on the interface between
process modeling and event data gathering. In the search for process models that best fit to …

Many current approaches to the design of intrusion detection systems apply feature
selection in a static, non-adaptive fashion. These methods often neglect the dynamic nature …