Process mining enables the reconstruction and evaluation of business processes based on
digital traces in IT systems. An increasingly important technique in this context is process …

Abstract Machine learning (ML) provides algorithms to create computer programs based on
data without explicitly programming them. In business process management (BPM), ML …

The main purpose of this paper is to provide information on how to create a convolutional
neural network (CNN) for extracting features from EEG signals. Our task was to understand …

Predictive monitoring of business processes is concerned with the prediction of ongoing
cases on a business process. Lately, the popularity of deep learning techniques has …

Networks had an increasing impact on modern life since network cybersecurity has become
an important research field. Several machine learning techniques have been developed to …

The contemporary process-aware information systems possess the capabilities to record the
activities generated during the process execution. To leverage these process specific fine …

Predictive business process monitoring focuses on predicting future characteristics of a
running process using event logs. The foresight into process execution promises great …

Supply chain integration (SCI) is the degree to which a manufacturer strategically
collaborates with its supply chain partners and collaboratively manages intra-and inter …

Encoding methods are employed across several process mining tasks, including predictive
process monitoring, anomalous case detection, trace clustering, etc. These methods are …

Business process simulation is a well-known approach to estimate the impact of changes to
a process with respect to time and cost measures–a practice known as what-if process …