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Sola, D., Warmuth, C., Schäfer, B., Badakhshan, P., Rehse, J.-R. and Kampik, T. (2023). SAP Signavio Academic Models: A large process model dataset.
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Abb, L., Bormann, C., der Aa, H. and Rehse, J.-R. (2022). Trace clustering for user behavior mining.
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Abb, L. and Rehse, J.-R. (2022). A reference data model for process-related user interaction logs.
In , Business Process Management : 20th International Conference, BPM 2022, Münster, Germany, September 11–16, 2022, proceedings (S. 57–74). Lecture Notes in Computer Science,
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Agostinelli, S., Marrella, A., Abb, L. and Rehse, J.-R. (2022). Mastering robotic process automation with process mining.
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Fellmann, M., Laue, R., Lantow, B. and Rehse, J.-R. (2021). Stand, Herausforderungen und Impulse des Geschäftsprozessmanagements.
In , Informatik 2020 – Back to the future : 50. Jahrestagung der Gesellschaft für Informatik vom 28. September – 2. Oktober 2020, virtual (S. 587–589). GI-Edition : Lecture Notes in Informatics. Proceedings,
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Laue, R., Rehse, J.-R. and Schoormann, T. (2021). 7. Workshop zum Stand und den Herausforderungen des Geschäftsprozessmanagements.
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Pufahl, L. and Rehse, J.-R. (2021). Conformance checking with regulations – a research agenda.
In , EMISA 2021: Enterprise Modeling and Information Systems Architectures 2021 : Proceedings of the 11th International Workshop on Enterprise Modeling and Information Systems Architectures : Kiel, Germany, May 20–21, 2021 (S. 24–29). CEUR Workshop Proceedings,
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Striewe, M., Houy, C., Rehse, J.-R., Ullrich, M., Fettke, P., Schaper, N. and Oberweis, A. (2021). Towards an automated assessment of graphical (business process) modelling competences.
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Berrang, A., Houy, C., Rehse, J.-R. and Fettke, P. (2020). Prozessorientierte Schulung von Einsatzkräften für robotergestützte Rettungsmissionen der Feuerwehr.
In , Entwicklungen, Chancen und Herausforderungen der Digitalisierung : Proceedings der 15. Internationalen Tagung Wirtschaftsinformatik, WI 2020, Potsdam, Germany, March 9–11, 2020 (S. 153–167). ,
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Rebmann, A., Rehse, J.-R., Pinter, M., Schnaubelt, M., Daun, K. and Fettke, P. (2020). IoT-based task recognition for process assistance in human-robot disaster response.
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Rehse, J.-R., Striewe, M. and Ullrich, M. (2020). 2. Workshop zur Modellierung in der Hochschullehre.
In , MODELLIERUNG-C 2020 : Companion proceedings of Modellierung 2020 Short, Workshop and Tools & Demo Papers, co-located with Modellierung 2020, Vienna, Austria, February 19–21, 2020 (S. 56–57). CEUR Workshop Proceedings,
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Schuhmann, S., Rehse, J.-R., Baumann, S. and Fettke, P. (2020). Interactive process clustering with t-SNE.
In , BPM-D 2020 : Proceedings of the Best Dissertation Award, Doctoral Consortium, and Demonstration & Resources Track at BPM 2020 co-located with the 18th International Conference on Business Process Management (BPM 2020) Sevilla, Spain, September 13–18, 2020 (S. 82–86). CEUR Workshop Proceedings,
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Zandkarimi, F., Rehse, J.-R., Soudmand, P. and Höhle, H. (2020). A generic framework for trace clustering in process mining.
In , 2nd International Conference on Process Mining (ICPM) : Virtual conference, 4–9 October 2020, Padua, Italy, proceedings (S. 177–184). 2020 2nd International Conference on Process Mining (ICPM),
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Hake, P., Rehse, J.-R. and Fettke, P. (2019). Supporting complaint management in the medical technology industry by means of deep learning.
In , Business Process Management Workshops : BPM 2019 International Workshops, Vienna, Austria, September 1–6, 2019, Revised Selected Papers (S. 56–67). Lecture Notes in Business Information Processing : LNBIP,
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Rehse, J.-R. and Fettke, P. (2019). Clustering business process activities for identifying reference model components.
In , Business Process Management Workshops : BPM 2018 International Workshops, Sydney, NSW, Australia, September 9–14, 2018, Revised Papers (S. 5–17). Lecture Notes in Business Information Processing : LNBIP,
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Rehse, J. (2018). Situational reference model mining.
In , CAiSE-DC 2018 : Proceedings of the Doctoral Consortium, papers presented at the 30th International Conference on Advanced Information Systems Engineering (CAiSE 2018) Tallinn, Estonia, June 11–15, 2018 (S. 28–36). CEUR Workshop Proceedings,
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Rehse, J.-R. and Fettke, P. (2018). Process mining crimes – a threat to the validity of process discovery evaluations.
In , Business Process Management Forum : BPM Forum 2018, Sydney, NSW, Australia, September 9–14, 2018, Proceedings (S. 3–19). Lecture Notes in Business Information Processing : LNBIP,
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Tenschert, J., Rehse, J.-R., Fettke, P. and Lenz, R. (2018). Speech acts in actual processes: Evaluation of interfaces and triggers in ITIL.
In , Business Process Management Workshops : BPM 2017 International Workshops, Barcelona, Spain, September 10–11, 2017, Revised Papers (S. 348–360). Lecture Notes in Business Information Processing : LNBIP,
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Evermann, J., Rehse, J.-R. and Fettke, P. (2017). XES Tensorflow – process prediction using the Tensorflow deep-learning framework.
In , Advanced information systems engineering : 29th International Conference CAiSE 2017, Essen, Germany, June 12–16, 2017 : proceedings of CAiSE Forum and Doctoral Consortium papers (S. 41–48). CEUR Workshop Proceedings,
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Evermann, J., Rehse, J.-R. and Fettke, P. (2016). A deep learning approach for predicting process behaviour at runtime.
In , Business Process Management Workshops : BPM 2016 International Workshops, Rio de Janeiro, Brazil, September 19, 2016, Revised Papers (S. 327–338). Lecture Notes in Business Information Processing : LNBIP,
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Rehse, J.-R. and Fettke, P. (2016). Mining reference process models from large instance data.
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Rehse, J.-R., Fettke, P. and Loos, P. (2016). An execution-semantic approach to inductive reference models development.
In , 24th European Conference on Information Systems, ECIS 2016 : Istanbul, Turkey, June 12–15, 2016 (S. Paper 80). Lecture Notes in Business Information Processing : LNBIP,
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