Sandra Zilker
Sandra Zilker
Verified email at
Cited by
Cited by
Prescriptive business process monitoring for recommending next best actions
S Weinzierl, S Dunzer, S Zilker, M Matzner
International conference on business process management, 193-209, 2020
XNAP: making LSTM-based next activity predictions explainable by using LRP
S Weinzierl, S Zilker, J Brunk, K Revoredo, M Matzner, J Becker
International Conference on Business Process Management, 129-141, 2020
A next click recommender system for web-based service analytics with context-aware LSTMs
S Weinzierl, M Stierle, S Zilker, M Matzner
An empirical comparison of deep-neural-network architectures for next activity prediction using context-enriched process event logs
S Weinzierl, S Zilker, J Brunk, K Revoredo, A Nguyen, M Matzner, ...
arXiv preprint arXiv:2005.01194, 2020
From predictive to prescriptive process monitoring: Recommending the next best actions instead of calculating the next most likely events.
S Weinzierl, S Zilker, M Stierle, M Matzner, G Park
Wirtschaftsinformatik (Zentrale Tracks), 364-368, 2020
The influence of algorithm aversion and anthropomorphic agent design on the acceptance of AI-based job recommendations.
J Ochmann, L Michels, S Zilker, V Tiefenbeck, S Laumer
ICIS, 2020
The evaluation of the black box problem for AI-based recommendations: An interview-based study
J Ochmann, S Zilker, S Laumer
International Conference on Wirtschaftsinformatik, 232-246, 2021
The Status Quo of Process Mining in the Industrial Sector
S Dunzer, S Zilker, E Marx, V Grundler, M Matzner
International Conference on Wirtschaftsinformatik, 629-644, 2021
Bringing light into the darkness-A systematic literature review on explainable predictive business process monitoring techniques
M Stierle, J Brunk, S Weinzierl, S Zilker, M Matzner, J Becker
Predictive business process deviation monitoring
S Weinzierl, S Dunzer, J Tenschert, S Zilker, M Matzner
Proceedings of the 29th European Conference on Information Systems (ECIS), 2021
Job Seekers' Artificial Intelligence-related Black Box Concerns
J Ochmann, S Zilker, S Laumer
Proceedings of the 2020 on Computers and People Research Conference, 101-102, 2020
Design principles for comprehensible process discovery in process mining
M Stierle, S Zilker, S Dunzer, JC Tenscher, G Karagegova
GAM (e) changer or not? An evaluation of interpretable machine learning models based on additive model constraints
P Zschech, S Weinzierl, N Hambauer, S Zilker, M Kraus
arXiv preprint arXiv:2204.09123, 2022
Process Mining for Advanced Service Analytics–From Process Efficiency to Customer Encounter and Experience
S Zilker, E Marx, M Stierle, M Matzner
Designing a Method for Resource-specific Next Activity Prediction
S Zilker
PACIS 2022 Proceedings, 2022
A Method for Predicting Workarounds in Business Processes
S Weinzierl, C Bartelheimer, S Zilker, D Beverungen, M Matzner
XNAP: Making LSTM-Based Next Activity Predictions Explainable by Using LRP
M Matzner, J Becker
Business Process Management Workshops: BPM 2020 International Workshops …, 2021
AIS Electronic Library (AISeL)
M Stierle, J Brunk, S Weinzierl, S Zilker, M Matzner
Text-Aware Predictive Process Monitoring with Contextualized Word Embeddings
L Cabrera, S Weinzierl, S Zilker, M Matzner
Prescriptive Business Process Monitoring for Recommending Next Best Actions
M Matzner
The system can't perform the operation now. Try again later.
Articles 1–20