Former Research Assistant
Chair of Information Systems and Information Management
Leonardo Campus 3
48149
Münster
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Leonardo Campus 3
48149
Münster
Niemann, M., Assenmacher, D., Brunk, J., Riehle, D. M., Becker, J., & Trautmann, H. (2022). (Semi-)Automatische Kommentarmoderation zur Erhaltung Konstruktiver Diskurse. In Weitzel, G., & Mündges, S. (Eds.), Hate Speech — Definitionen, Ausprägungen, Lösungen (pp. 249–274). Wiesbaden: VS Verlag für Sozialwissenschaften.
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Stierle, M., Brunk, J., Weinzierl, S., Zilker, S., Matzner, M., & Becker, J. (2021). Bringing Light Into the Darkness — A Systematic Literature Review on Explainable Predictive Business Process Monitoring Techniques. In Proceedings of the European Conference on Information Systems 2021, Marrackech, Morocco.
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Wolf, F., Brunk, J., & Becker, J. (2021). A Framework of Business Process Monitoring and Prediction Techniques. In Proceedings of the International Conference on Wirtschaftsinformatik 2021, Duisburg-Essen, Germany.
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Brunk, J., Stierle, M., Papke, L., Revoredo, K., Matzner, M., & Becker, J. (2021). Cause vs. Effect in Context-Sensitive Prediction of Business Process Instances. Information Systems, 95(1).
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Brunk, J. (2021). Prediction of Business Processes — Selection and Development of Interpretable Machine Learning-based Next Activity Prediction Techniques. at the Universität Münster. Münster: Selbstverlag — Eigenverlag.
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Becker, J., Brunk, J., Ding, W., & Niemann, M. (2020). Conceptualization of an Integrated Procedure Model for Business Process Monitoring and Prediction. In Proceedings of the Conference on Business Informatics 2020, Antwerp, Belgium.
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Brunk, J. (2020). Structuring Business Process Context Information for Process Monitoring and Prediction. In Proceedings of the Conference on Business Informatics 2020, Antwerp, Belgium.
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Brunk, J., Methner, C., Cordes, A.-K., Thiermann, S., & Goerke, T. (2020). Trace Clustering for an Online Freight Exchange at TIMOCOM. In Proceedings of the International Conference on Business Process Management 2020 — BPM Industry Forum, Sevilla, Spain.
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Jorgensen, M., Choi, M., Niemann, M., Brunk, J., & Becker, J. (2020). Multi-Class Detection of Abusive Language Using Automated Machine Learning. In Proceedings of the 15. Internationale Tagung Wirtschaftsinformatik (WI 2020), Potsdam, Germany.
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Niemann, M., Riehle, D. M., Brunk, J., & Becker, J. (2020). What is Abusive Language? — Integrating Different Views on Abusive Language for Machine Learning. In Grimme, C., Preuss, M., Takes, F., & Waldherr, A. (Eds.), Disinformation in Open Online Media — MISDOOM 2019 (pp. 59–73). Lecture Notes in Computer Science: Vol. 12021. Springer.
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Niemann, M., Welsing, J., Riehle, D. M., Brunk, J., Assenmacher, D., & Becker, J. (2020). Abusive Comments in Online Media and How to Fight Them: State of the Domain and a Call to Action. In Proceedings of the 2nd Multidisciplinary International Symposium on Disinformation in Open Online Media, Leiden, Netherlands, 122–137.
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Riehle, D. M., Niemann, M., Brunk, J., Assenmacher, D., Trautmann, H., & Becker, J. (2020). Building an Integrated Comment Moderation System — Towards a Semi-Automatic Moderation tool. In Proceedings of the HCI International 2020, Copenhagen, Denmark.
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Weinzierl, S., Zilker, S., Brunk, J., Revoredo, K., Matzner, M., & Becker, J. (2020). XNAP: Making LSTM-based Next Activity Predictions Explainable by Using LRP. In Proceedings of the International Conference on Business Process Management 2020 — 4th International Workshop in Artificial Intelligence for Business Process Management, Sevilla, Spain.
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Brunk, J., Stottmeister, J., Weinzierl, S., Matzner, M., & Becker, J. (2020). Exploring the Effect of Context Information on Deep Learning Business Process Predictions. Journal of Decision Systems, 2020(Special Issue IFIP DSS 2020).
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Brunk, J., Mattern, J., & Riehle, D. M. (2019). Effect of Transparency and Trust on Acceptance of Automatic Online Comment Moderation Systems. In Proceedings of the Conference on Business Informatics (CBI2019), Moscow, Russia, 429–435.
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Brunk, J., Niemann, M., & Riehle, D. M. (2019). Can Analytics as a Service Save the Online Discussion Culture? — The Case of Comment Moderation in the Media Industry. In Proceedings of the Conference on Business Informatics (CBI2019), Moscow, Russia, 472–481.
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Niemann, M., Riehle, D. M., Brunk, J., & Becker, J. (2019). What is Abusive Language? — Integrating Different Views on Abusive Language for Machine Learning. Poster session presented at the Multidisciplinary International Symposium on Disinformation in Open Online Media, Hamburg, Germany.
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Brunk, J., Revoredo, K., Stierle, M., Matzner, M., Delfmann, P., & Becker, J. (2018). Prediction of Business Process Instances with Dynamic Bayesian Networks. In Ceravolo, P., Gómez, L. M. T., & Van, K. M. (Eds.), Proceedings of the 8th International Symposium on Data-driven Process Discovery and Analysis (SIMPDA 2018) (pp. 50–54). Sevilla, Spanien: CEUR Workshop Proceedings.
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Brunk, J., Riehle, D. M., & Delfmann, P. (2018). Prediction of Customer Movements in Large Tourism Industries by the Means of Process Mining. In Proceedings of the European Conference on Information Systems (ECIS 2018), Portsmouth, UK.
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Riehle, D. M., Höhenberger, S., Brunk, J., Delfmann, P., & Becker, J. (2017). [εm] — Process Analysis using a Meta Modeling Tool. In Proceedings of the Conceptual Modeling Demos (ER Demos 2017), Valencia, Spain, 334–337.
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Riemer, K., Gal, U., Brunk, J., Gilchriest, B., Ord, R., & Tong, J.-A. (2014). Australian Digital Commerce: Now is the Time for Australian Retailers to Address the Customer Engagement Gap. In Australian Digital Transformation Lab: Vol. 2. Sydney, Australia.
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Riemer, K., Brunk, J., Gal, U., Gilchriest, B., & Ord, R. (2013). Australian Digital Commerce: A commentary on the retail sector. In Australian Digital Transformation Lab: Vol. 1. Sydney, Australia.
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