Dr. Sven Weinzierl

2023

• Oberdorf F., Schaschek M., Weinzierl S., Stein N., Matzner M., Flath C.:
  Predictive end-to-end enterprise process network monitoring
  In: Business & Information Systems Engineering (2023)
  ISSN: 1867-0202
  DOI: 10.1007/s12599-022-00778-4
  BibTeX: Download

2022

• Weinzierl S., Wolf V., Pauli T., Beverungen D., Matzner M.:
  Detecting temporal workarounds in business processes – A deep-learning-based method for analysing event log data
  In: Journal of Business Analytics 5 (2022), S. 76-100
  ISSN: 2573-234X
  DOI: 10.1080/2573234X.2021.1978337
  URL: https://www.tandfonline.com/doi/full/10.1080/2573234X.2021.1978337
  BibTeX: Download

2021

• Stierle M., Weinzierl S., Harl M., Matzner M.:
  A technique for determining relevance scores of process activities using graph-based neural networks
  In: Decision Support Systems 144 (2021), Art.Nr.: 113511
  ISSN: 0167-9236
  DOI: 10.1016/j.dss.2021.113511
  URL: http://www.sciencedirect.com/science/article/pii/S016792362100021X
  BibTeX: Download

2020

• Brunk J., Stottmeister J., Weinzierl S., Matzner M., Becker J.:
  Exploring the effect of context information on deep learning business process predictions
  In: Journal of Decision Systems (2020), S. 1-16
  ISSN: 1246-0125
  DOI: 10.1080/12460125.2020.1790183
  BibTeX: Download
• Harl M., Weinzierl S., Stierle M., Matzner M.:
  Explainable predictive business process monitoring using gated graph neural networks
  In: Journal of Decision Systems (2020), S. 1-16
  ISSN: 1246-0125
  DOI: 10.1080/12460125.2020.1780780
  BibTeX: Download

2023

• Drodt C., Weinzierl S., Matzner M., Delfmann P.:
  Predictive Recommining: Learning relations between event log characteristics and machine learning approaches for supporting predictive process monitoring
  International Conference on Advanced Information Systems Engineering (Zaragoza, 12. Juni 2023 - 16. Juni 2023)
  In: Proceedings of the 35th International Conference on Advanced Information Systems Engineering Forum 2023
  BibTeX: Download
• Zilker S., Weinzierl S., Zschech P., Kraus M., Matzner M.:
  Best of both worlds: Combining predictive power with interpretable and explainable results for patient pathway prediction
  European Conference on Information Systems (Kristiansand, 13. Juni 2023 - 16. Juni 2023)
  In: Proceedings of the 31st European Conference on Information Systems 2023
  BibTeX: Download

2022

• Cabrera Pérez L., Weinzierl S., Zilker S., Matzner M.:
  Text-aware predictive process monitoring with contextualized word embeddings
  International Conference on Business Process Management (Münster)
  In: Proceedings of the BPM 2022 International Workshops 2022
  DOI: 10.1007/978-3-031-25383-6_22
  BibTeX: Download
• Weinzierl S., Bartelheimer C., Zilker S., Beverungen D., Matzner M.:
  A method for predicting workarounds in business processes
  Pacific Asia Conference on Information Systems (Taipei-Sydney, 5. Juli 2022 - 9. Juli 2022)
  In: Proceedings of the 25th Pacific Asia Conference on Information Systems 2022
  BibTeX: Download
• Zschech P., Weinzierl S., Hambauer N., Zilker S., Kraus M.:
  GAM(e) changer or not? An evaluation of interpretable machine learning models based on additive model constraints
  European Conference on Information Systems (Timisoara, 5. Juli 2022 - 9. Juli 2022)
  In: Proceedings of the 30th European Conference on Information Systems 2022
  BibTeX: Download

2021

• Drodt C., Weinzierl S., Matzner M., Delfmann P.:
  The recomminder: A decision support tool for predictive business process monitoring
  International Conference on Business Process Management (Rom)
  In: Proceedings of the BPM 2021 Demonstration & Resources Track, Best BPM Dissertation Award, and Doctoral Consortium 2021
  BibTeX: Download
• Stierle M., Brunk J., Weinzierl S., Zilker S., Matzner M., Becker J.:
  Bringing light into the darkness - A systematic literature review on explainable predictive business process monitoring techniques
  European Conference on Information Systems (Marrakesch)
  In: Proceedings of the 29th European Conference on Information Systems 2021
  BibTeX: Download
• Weinzierl S.:
  Exploring gated graph sequence neural networks for predicting next process activities
  International Conference on Business Process Management (Rom)
  In: Proceedings of the BPM 2021 International Workshops. 2021
  BibTeX: Download
• Weinzierl S., Dunzer S., Tenschert J., Zilker S., Matzner M.:
  Predictive business process deviation monitoring
  European Conference on Information Systems (Marrakesch)
  In: Proceedings of the 29th European Conference on Information Systems 2021
  BibTeX: Download

2020

• Marx E., Stierle M., Weinzierl S., Matzner M.:
  Closing the gap between smart manufacturing applications and data management
  International Conference on Wirtschaftsinformatik (WI) (Potsdam, 9. März 2020 - 11. März 2020)
  In: Proceedings of the 15th International Conference on Wirtschaftsinformatik (WI) 2020
  DOI: 10.30844/wi_2020_u1-marx
  URL: https://library.gito.de/2021/07/wi2020-community-tracks-9/
  BibTeX: Download
• Nguyen A., Chatterjee S., Weinzierl S., Schwinn L., Matzner M., Eskofier B.:
  Time matters: Time-aware LSTMs for predictive business process monitoring
  International Conference on Process Mining (Padua, 4. Oktober 2020 - 9. Oktober 2020)
  In: Proceedings of the ICPM 2020 International Workshops 2020
  BibTeX: Download
• Weinzierl S., Dunzer S., Zilker S., Matzner M.:
  Prescriptive business process monitoring for recommending next best actions
  International Conference on Business Process Management (Sevilla, 13. September 2020 - 18. September 2020)
  In: Proceedings of the 18th International Conference on Business Process Management Forum 2020
  DOI: 10.1007/978-3-030-58638-6_12
  URL: https://link.springer.com/content/pdf/10.1007/978-3-030-58638-6_12.pdf
  BibTeX: Download
• Weinzierl S., Stierle M., Zilker S., Matzner M.:
  A next click recommender system for web-based service analytics with context-aware LSTMs
  Hawaii International Conference on System Sciences (Grand Wailea, Maui, Hawaii, 7. Januar 2020 - 10. Januar 2020)
  In: Proceedings of the 53rd Hawaii International Conference on System Sciences 2020
  DOI: 10.24251/HICSS.2020.190
  URL: http://hdl.handle.net/10125/63929
  BibTeX: Download
• Weinzierl S., Wolf V., Pauli T., Beverungen D., Matzner M.:
  Detecting workarounds in business processes — A deep learning method for analyzing event logs
  European Conference on Information Systems (Marrakesch, 15. Juni 2020 - 17. Juni 2020)
  In: Proceedings of the 28th European Conference on Information Systems 2020
  URL: https://www.researchgate.net/publication/341180737_DETECTING_WORKAROUNDS_IN_BUSINESS_PROCESSES_-_A_DEEP_LEARNING_METHOD_FOR_ANALYZING_EVENT_LOGS
  BibTeX: Download
• Weinzierl S., Zilker S., Brunk J., Revoredo K., Matzner M., Becker J.:
  XNAP: Making LSTM-based next activity predictions explainable by using LRP
  International Conference on Business Process Management (Sevilla, 13. September 2020 - 18. September 2020)
  In: Proceedings of the BPM 2020 International Workshops. 2020
  DOI: 10.1007/978-3-030-66498-5_10
  BibTeX: Download
• Weinzierl S., Zilker S., Stierle M., Park G., Matzner M.:
  From predictive to prescriptive process monitoring: Recommending the next best actions instead of calculating the next most likely events
  Internationale Tagung Wirtschaftsinformatik (Potsdam, 8. März 2020 - 11. März 2020)
  In: Proceedings of the 15th International Conference on Wirtschaftsinformatik 2020
  DOI: 10.30844/wi_2020_c12-weinzierl
  URL: https://library.gito.de/open-access-pdf/C12_Prescriptive_process_monitoring_-_a_technique_for_determining_next_best_actions_resub.pdf
  BibTeX: Download

2019

• Weinzierl S., Revoredo K., Matzner M.:
  Predictive business process monitoring with context information from documents
  European Conference on Information Systems (Stockholm, 8. Juni 2019 - 14. Juni 2019)
  In: Proceedings of the 27th European Conference on Information Systems 2019
  URL: https://www.researchgate.net/publication/333245929_PREDICTIVE_BUSINESS_PROCESS_MONITORING_WITH_CONTEXT_INFORMATION_FROM_DOCUMENTS
  BibTeX: Download