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Jens Brunk
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2020 – today
- 2024
- [c15]Sven Weinzierl, Sandra Zilker, Jens Brunk, Kate Revoredo, Martin Matzner, Jörg Becker:
Context-aware Explanations of Accurate Predictions in Service Processes. HICSS 2024: 1498-1507 - 2021
- [b1]Jens Brunk:
Prediction of business processes: selection and development of interpretable machine learning-based next activity prediction techniques. University of Münster, Germany, 2021, pp. 1-362 - [j2]Jens Brunk
, Matthias Stierle, Leon Papke, Kate Revoredo
Cause vs. effect in context-sensitive prediction of business process instances. Inf. Syst. 95: 101635 (2021) - [c14]Matthias Stierle, Jens Brunk, Sven Weinzierl, Sandra Zilker, Martin Matzner, Jörg Becker:
Bringing Light Into the Darkness - A Systematic Literature Review on Explainable Predictive Business Process Monitoring Techniques. ECIS 2021 - [c13]Frederik Wolf, Jens Brunk, Jörg Becker:
A Framework of Business Process Monitoring and Prediction Techniques. Wirtschaftsinformatik 2021 - 2020
- [j1]Jens Brunk
Exploring the effect of context information on deep learning business process predictions. J. Decis. Syst. 29(Supplement): 328-343 (2020) - [c12]Sven Weinzierl
XNAP: Making LSTM-Based Next Activity Predictions Explainable by Using LRP. Business Process Management Workshops 2020: 129-141 - [c11]Dennis M. Riehle
Building an Integrated Comment Moderation System - Towards a Semi-automatic Moderation Tool. HCI (15) 2020: 71-86 - [c10]Marco Niemann
Abusive Comments in Online Media and How to Fight Them - State of the Domain and a Call to Action. MISDOOM 2020: 122-137 - [c9]Jens Brunk:
Structuring Business Process Context Information for Process Monitoring and Prediction. CBI (1) 2020: 39-48 - [c8]Jörg Becker, Jens Brunk, Wenying Ding, Marco Niemann:
Conceptualization of an Integrated Procedure Model for Business Process Monitoring and Prediction. CBI (1) 2020: 49-57 - [c7]Mackenzie Jorgensen
Multi-Class Detection of Abusive Language Using Automated Machine Learning. Wirtschaftsinformatik (Zentrale Tracks) 2020: 1763-1775 - [i3]Sven Weinzierl, Sandra Zilker, Jens Brunk, Kate Revoredo, An Nguyen, Martin Matzner, Jörg Becker, Björn M. Eskofier:
An empirical comparison of deep-neural-network architectures for next activity prediction using context-enriched process event logs. CoRR abs/2005.01194 (2020) - [i2]Jens Brunk, Matthias Stierle, Leon Papke, Kate Revoredo, Martin Matzner, Jörg Becker:
Cause vs. Effect in Context-Sensitive Prediction of Business Process Instances. CoRR abs/2007.07549 (2020) - [i1]Sven Weinzierl, Sandra Zilker, Jens Brunk, Kate Revoredo, Martin Matzner, Jörg Becker:
XNAP: Making LSTM-based Next Activity Predictions Explainable by Using LRP. CoRR abs/2008.07993 (2020)
2010 – 2019
- 2019
- [c6]Marco Niemann
What Is Abusive Language? MISDOOM 2019: 59-73 - [c5]Jens Brunk, Jana Mattern, Dennis M. Riehle
Effect of Transparency and Trust on Acceptance of Automatic Online Comment Moderation Systems. CBI (1) 2019: 429-435 - [c4]Jens Brunk, Marco Niemann, Dennis M. Riehle
Can Analytics as a Service Save the Online Discussion Culture? - The Case of Comment Moderation in the Media Industry. CBI (1) 2019: 472-481 - 2018
- [c3]Jens Brunk, Dennis M. Riehle, Patrick Delfmann:
Prediction of Customer Movements in Large Tourism Industries by the Means of Process Mining. ECIS 2018: 40 - [c2]Jens Brunk, Kate Revoredo, Matthias Stierle, Martin Matzner, Patrick Delfmann, Jörg Becker:
Prediction of Business Process Instances with Dynamic Bayesian Networks. SIMPDA 2018: 50-54 - 2017
- [c1]Dennis M. Riehle, Steffen Höhenberger, Jens Brunk, Patrick Delfmann, Jörg Becker:
[εm] - Process Analysis using a Meta Modeling Tool. ER Forum/Demos 2017: 334-337
Coauthor Index
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