[εm] - Process Analysis using a Meta Modeling Tool. - Dennis M. Riehle; Steffen Höhenberger; Jens Brunk; Patrick Delfmann; Jörg Becker 001 (ER Forum/Demos, 2017)

Prediction of Customer Movements in Large Tourism Industries by the Means of Process Mining. - Jens Brunk; Dennis M. Riehle; Patrick Delfmann (ECIS, 2018)

Prediction of Business Process Instances with Dynamic Bayesian Networks. - Jens Brunk; Kate Revoredo; Matthias Stierle; Martin Matzner; Patrick Delfmann; Jörg Becker 001 (SIMPDA, 2018)

What Is Abusive Language? - Marco Niemann; Dennis M. Riehle; Jens Brunk; Jörg Becker 001 (MISDOOM, 2019)

Effect of Transparency and Trust on Acceptance of Automatic Online Comment Moderation Systems. - Jens Brunk; Jana Mattern; Dennis M. Riehle (CBI (1), 2019)

Can Analytics as a Service Save the Online Discussion Culture? - The Case of Comment Moderation in the Media Industry. - Jens Brunk; Marco Niemann; Dennis M. Riehle (CBI (1), 2019)

XNAP: Making LSTM-Based Next Activity Predictions Explainable by Using LRP. - Sven Weinzierl; Sandra Zilker; Jens Brunk; Kate Revoredo; Martin Matzner; Jörg Becker 001 (Business Process Management Workshops, 2020)

Building an Integrated Comment Moderation System - Towards a Semi-automatic Moderation Tool. - Dennis M. Riehle; Marco Niemann; Jens Brunk; Dennis Assenmacher; Heike Trautmann; Jörg Becker 001 (HCI (15), 2020)

Abusive Comments in Online Media and How to Fight Them - State of the Domain and a Call to Action. - Marco Niemann; Jens Welsing; Dennis M. Riehle; Jens Brunk; Dennis Assenmacher; Jörg Becker 001 (MISDOOM, 2020)

Conceptualization of an Integrated Procedure Model for Business Process Monitoring and Prediction. - Jörg Becker 001; Jens Brunk; Wenying Ding; Marco Niemann (CBI (1), 2020)

Structuring Business Process Context Information for Process Monitoring and Prediction. - Jens Brunk (CBI (1), 2020)

Multi-Class Detection of Abusive Language Using Automated Machine Learning. - Mackenzie Jorgensen; Minho Choi; Marco Niemann; Jens Brunk; Jörg Becker 001 (Wirtschaftsinformatik (Zentrale Tracks), 2020)

An empirical comparison of deep-neural-network architectures for next activity prediction using context-enriched process event logs. - Sven Weinzierl; Sandra Zilker; Jens Brunk; Kate Revoredo; An Nguyen; Martin Matzner; Jörg Becker 001; Björn M. Eskofier (CoRR, 2020)

Exploring the effect of context information on deep learning business process predictions. - Jens Brunk; Johannes Stottmeister; Sven Weinzierl; Martin Matzner; Jörg Becker 001 (J. Decis. Syst., 2020)

Bringing Light Into the Darkness - A Systematic Literature Review on Explainable Predictive Business Process Monitoring Techniques. - Matthias Stierle; Jens Brunk; Sven Weinzierl; Sandra Zilker; Martin Matzner; Jörg Becker 001 (ECIS, 2021)

A Framework of Business Process Monitoring and Prediction Techniques. - Frederik Wolf; Jens Brunk; Jörg Becker 001 (Wirtschaftsinformatik, 2021)

Cause vs. effect in context-sensitive prediction of business process instances. - Jens Brunk; Matthias Stierle; Leon Papke; Kate Revoredo; Martin Matzner; Jörg Becker 001 (Inf. Syst., 2021)

Prediction of business processes: selection and development of interpretable machine learning-based next activity prediction techniques. - Jens Brunk (2021)

Context-aware Explanations of Accurate Predictions in Service Processes. - Sven Weinzierl; Sandra Zilker; Jens Brunk; Kate Revoredo; Martin Matzner; Jörg Becker 001 (HICSS, 2024)