Summary of Machine Learning in Business Process Management: a Systematic Literature Review, by Sven Weinzierl et al.
Machine learning in business process management: A systematic literature review
by Sven Weinzierl, Sandra Zilker, Sebastian Dunzer, Martin Matzner
First submitted to arxiv on: 26 May 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: None
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper presents the first comprehensive review of machine learning (ML) applications in business process management (BPM). It organises knowledge from various literature streams under BPM task phases, explaining how ML helps perform tasks and identifying technical commonalities. The study aims to facilitate cumulative research by providing a roadmap for future studies and helping managers/consultants identify relevant ML applications. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper reviews machine learning in business process management. It shows how ML can help with decision-making, modeling processes, and resource allocation. The authors collect tasks from different sources and group them into phases of the process lifecycle. They explain how ML helps perform these tasks and find commonalities in implementations. This study is useful for researchers who want to combine existing approaches or develop new ones. |
Keywords
* Artificial intelligence * Machine learning
