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ORCIDSandra Zilker
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2020 – today
- 2024
[j1]Sven Weinzierl
, Sandra Zilker, Sebastian Dunzer, Martin Matzner:
Machine learning in business process management: A systematic literature review. Expert Syst. Appl. 253: 124181 (2024)- [c23]Maximilian Victor Harl, Sandra Zilker, Sven Weinzierl:
Towards Automated Business Process Redesign in Runtime Using Generative Machine Learning. ECIS 2024 - [c22]Annina Liessmann, Weixin Wang, Sven Weinzierl, Sandra Zilker, Martin Matzner:
Transfer Learning for Predictive Process Monitoring. ECIS 2024 - [c21]Annina Liessmann, Sandra Zilker, Sven Weinzierl, Maria Sukhareva, Martin Matzner:
Predicting Customer Satisfaction in Service Processes Using Multilingual Large Language Models. HICSS 2024: 1488-1497 - [c20]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 - [c19]Sven Weinzierl, Sandra Zilker, Patrick Zschech, Mathias Kraus, Tobias Leibelt, Martin Matzner:
How Risky is my AI System? A Method for Transparent Classification of AI System Descriptions by Regulated AI Risk Categories. ICIS 2024 - [i7]Sandra Zilker, Sven Weinzierl, Mathias Kraus, Patrick Zschech, Martin Matzner:
A machine learning framework for interpretable predictions in patient pathways: The case of predicting ICU admission for patients with symptoms of sepsis. CoRR abs/2405.13187 (2024) - [i6]Sven Weinzierl, Sandra Zilker, Sebastian Dunzer, Martin Matzner:
Machine learning in business process management: A systematic literature review. CoRR abs/2405.16396 (2024) - [i5]Sven Kruschel, Nico Hambauer, Sven Weinzierl, Sandra Zilker, Mathias Kraus, Patrick Zschech:
Challenging the Performance-Interpretability Trade-off: An Evaluation of Interpretable Machine Learning Models. CoRR abs/2409.14429 (2024) - 2023
- [c18]Sebastian Dunzer, Willi Tang, Nico Höchstädter, Sandra Zilker, Martin Matzner:
Design Principles for Using Business Process Management Systems. Business Process Management Workshops 2023: 217-228 - [c17]Sandra Zilker, Sven Weinzierl, Patrick Zschech, Mathias Kraus, Martin Matzner:
Best of Both Worlds: Combining Predictive Power with Interpretable and Explainable Results for Patient Pathway Prediction. ECIS 2023 - 2022
- [c16]Lena M. Cabrera, Sven Weinzierl, Sandra Zilker, Martin Matzner:
Text-Aware Predictive Process Monitoring with Contextualized Word Embeddings. Business Process Management Workshops 2022: 303-314 - [c15]Patrick Zschech, Sven Weinzierl, Nico Hambauer, Sandra Zilker, Mathias Kraus:
GAM(e) changer or not? An evaluation of interpretable machine learning models based on additive model constraints. ECIS 2022 - [c14]Sandra Zilker, Emanuel Marx, Matthias Stierle, Martin Matzner:
Process Mining for Advanced Service Analytics - From Process Efficiency to Customer Encounter and Experience. HICSS 2022: 1-10 - [c13]Sandra Zilker:
Designing a Method for Resource-specific Next Activity Prediction. PACIS 2022: 72 - [c12]Sven Weinzierl, Christian Bartelheimer, Sandra Zilker, Daniel Beverungen, Martin Matzner:
A Method for Predicting Workarounds in Business Processes. PACIS 2022: 108 - [i4]Patrick Zschech, Sven Weinzierl, Nico Hambauer, Sandra Zilker, Mathias Kraus:
GAM(e) changer or not? An evaluation of interpretable machine learning models based on additive model constraints. CoRR abs/2204.09123 (2022) - 2021
- [c11]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 - [c10]Sven Weinzierl, Sebastian Dunzer, Johannes Christian Tenschert, Sandra Zilker, Martin Matzner:
Predictive Business Process Deviation Monitoring. ECIS 2021 - [c9]Sebastian Dunzer, Sandra Zilker, Emanuel Marx, Valentin Grundler, Martin Matzner:
The Status Quo of Process Mining in the Industrial Sector. Wirtschaftsinformatik 2021 - [c8]Jessica Ochmann, Sandra Zilker, Sven Laumer:
The evaluation of the black box problem for AI-based recommendations: An interview-based study. Wirtschaftsinformatik 2021 - 2020
- [c7]Sven Weinzierl, Sandra Zilker, Jens Brunk, Kate Revoredo, Martin Matzner, Jörg Becker:
XNAP: Making LSTM-Based Next Activity Predictions Explainable by Using LRP. Business Process Management Workshops 2020: 129-141 - [c6]Sven Weinzierl, Sebastian Dunzer, Sandra Zilker, Martin Matzner:
Prescriptive Business Process Monitoring for Recommending Next Best Actions. BPM (Forum) 2020: 193-209 - [c5]Matthias Stierle, Sandra Zilker, Sebastian Dunzer, Johannes Christian Tenschert, Gergana Karagegova:
Design Principles for Comprehensible Process Discovery in Process Mining. ECIS 2020 - [c4]Sven Weinzierl, Matthias Stierle, Sandra Zilker, Martin Matzner:
A Next Click Recommender System for Web-based Service Analytics with Context-aware LSTMs. HICSS 2020: 1-10 - [c3]Jessica Ochmann, Leonard Michels, Sandra Zilker, Verena Tiefenbeck, Sven Laumer:
The influence of algorithm aversion and anthropomorphic agent design on the acceptance of AI-based job recommendations. ICIS 2020 - [c2]Jessica Ochmann, Sandra Zilker, Sven Laumer:
Job Seekers' Artificial Intelligence-related Black Box Concerns. SIGMIS-CPR 2020: 101-102 - [c1]Sven Weinzierl, Sandra Zilker, Matthias Stierle, Martin Matzner, Gyunam Park:
From predictive to prescriptive process monitoring: Recommending the next best actions instead of calculating the next most likely events. Wirtschaftsinformatik (Zentrale Tracks) 2020: 364-368 - [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]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) - [i1]Sven Weinzierl, Sebastian Dunzer, Sandra Zilker, Martin Matzner:
Prescriptive Business Process Monitoring for Recommending Next Best Actions. CoRR abs/2008.08693 (2020)
Coauthor Index
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last updated on 2024-11-21 21:24 CET by the dblp team
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