Bringing light into the darkness - A systematic literature review on explainable predictive business process monitoring techniques

Stierle M, Brunk J, Weinzierl S, Zilker S, Matzner M, Becker J (2021)

Publication Language: English

Publication Type: Conference contribution, Original article

Publication year: 2021

Pages Range: 1-12

Conference Proceedings Title: Proceedings of the 29th European Conference on Information Systems

Event location: Marrakesch

Abstract

Predictive business process monitoring (PBPM) provides a set of techniques to perform different prediction tasks in running business processes, such as the next activity, the process outcome, or the remaining time. Nowadays, deep-learning-based techniques provide more accurate predictive models. However, the explainability of these models has long been neglected. The predictive quality is essential for PBPM-based decision support systems, but also its explainability for human stakeholders needs to be considered. Explainable artificial intelligence (XAI) describes different approaches to make machine-learning-based techniques explainable. To examine the current state of explainable PBPM techniques, we perform a structured and descriptive literature review. We identify explainable PBPM techniques of the domain and classify them along with different XAI-related concepts: prediction purpose, intrinsically interpretable or post-hoc, evaluation objective, and evaluation method. Based on our classification, we identify trends in the domain and remaining research gaps.

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How to cite

APA:

Stierle, M., Brunk, J., Weinzierl, S., Zilker, S., Matzner, M., & Becker, J. (2021). Bringing light into the darkness - A systematic literature review on explainable predictive business process monitoring techniques. In Proceedings of the 29th European Conference on Information Systems (pp. 1-12). Marrakesch, MA.

MLA:

Stierle, Matthias, et al. "Bringing light into the darkness - A systematic literature review on explainable predictive business process monitoring techniques." Proceedings of the European Conference on Information Systems, Marrakesch 2021. 1-12.

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