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Process Mining for Unstructured Data: Challenges and Research Directions


The application of process mining for unstructured data might significantly elevate novel insights into disciplines where unstructured data is a common data format. To efficiently analyze unstructured data by process mining and to convey confidence into the analysis result, requires bridging multiple challenges. The purpose of this paper is to discuss these challenges, present initial solutions and describe future research directions. We hope that this article lays the foundations for future collaboration on this topic.


Koschmider, Agnes; Aleknonytė-Resch, Milda; Fonger, Frederik; Imenkamp, Christian; Lepsien, Arvid; Apaydin, Kaan; Janssen, Dominik; Langhammer, Dominic; Ziolkowski, Tobias; Zisgen, Yorck (2024): Process Mining for Unstructured Data: Challenges and Research Directions. Modellierung 2024. DOI: 10.18420/modellierung2024_012. Bonn: Gesellschaft für Informatik e.V.. PISSN: 1617-5468. ISBN: 978-3-88579-742-5. pp. 119-136. Business Processes. Potsdam, Germany. 12.-15. March 2024