Context-aware explanations of accurate predictions in service processes
Weinzierl S, Zilker S, Brunk J, Revoredo K, Matzner M, Becker J (2024)
Publication Language: English
Publication Type: Conference contribution, Conference Contribution
Publication year: 2024
Conference Proceedings Title: Proceedings of the 57th Hawaii International Conference on System Sciences
Event location: Waikiki, Honolulu, Hawaii
Abstract
The performance of a service process can be
improved by the early anticipation of future behavior,
such as predicting the next activity using predictive
business process monitoring (PBPM). Recent PBPM
techniques are based on deep neural networks
(DNNs) and consider the process context to create
accurate predictions. To provide explainability of
these predictions, model-agnostic explainable AI (XAI)
methods, for example, SHAP, can be used. However,
creating these explanations is time-consuming and,
therefore, not applicable to service processes where
customers are involved. In this paper, we propose a
context-aware DNN-based technique to efficiently create
meaningful explanations of next activity predictions
using layer-wise relevance propagation. We evaluate
the predictive quality and the explanation creation time,
using three real-life service event logs. Further, we
demonstrate its visual output, highlighting its utility for
end-users.
Authors with CRIS profile
Sven Weinzierl
Lehrstuhl für Digital Industrial Service Systems
Sandra Zilker
Lehrstuhl für Digital Industrial Service Systems
Martin Matzner
Lehrstuhl für Digital Industrial Service Systems
Related research project(s)
Involved external institutions
Germany (DE)How to cite
APA:
Weinzierl, S., Zilker, S., Brunk, J., Revoredo, K., Matzner, M., & Becker, J. (2024). Context-aware explanations of accurate predictions in service processes. In Proceedings of the 57th Hawaii International Conference on System Sciences. Waikiki, Honolulu, Hawaii, US.
MLA:
Weinzierl, Sven, et al. "Context-aware explanations of accurate predictions in service processes." Proceedings of the Hawaii International Conference on System Sciences, Waikiki, Honolulu, Hawaii 2024.
BibTeX: Download