Business process compliance is a key area of business process management and aims at
ensuring that processes obey to compliance constraints such as regulatory constraints or …

Events recorded during the execution of a business process can be used to train models to
predict, at run-time, the outcome of each execution of the process (aka case). In this setting …

Various methods using machine and deep learning have been proposed to tackle different
tasks in predictive process monitoring, forecasting for an ongoing case eg the most likely …

There is a growing need for empirical benchmarks that support researchers and
practitioners in selecting the best machine learning technique for given prediction tasks. In …

It is well-known that context impacts running instances of a process. Thus, defining and
using contextual information may help to improve the predictive monitoring of business …

Previous studies investigating the efficacy of long short-term memory (LSTM) recurrent
neural networks in predictive process monitoring and their ability to capture the underlying …

Predictive business process monitoring concerns the unfolding of ongoing process instance
executions. Recent work in this area frequently applies “blackbox” like methods which …

Event prediction is the ability of anticipating future events, ie, future real-world occurrences,
and aims to support the user in deciding on actions that change future events towards a …

For organizations, the promise of process mining is that they can generate additional value
from event data that their information systems collect. While case studies and guidelines …

Among many domains being disrupted by blockchains, supply chains are at the top, as they
naturally involve multi-party collaboration and regulatory restrictions spanning geographic …