This online repository hosts software implementation, additional details of evaluation experiments, and some experiment outputs concerned with the following research papers on the topic of learning execution contexts:
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BPM 2022: Paper published in the BPM 2022 conference proceedings. Cite as: Yang, J., Ouyang, C., ter Hofstede, A. H. M., & van der Aalst, W. M. P. (2022). No Time to Dice: Learning Execution Contexts from Event Logs for Resource-Oriented Process Mining. In C. Di Ciccio, R. M. Dijkman, A. del-Río-Ortega, & S. Rinderle-Ma (Eds.), Business Process Management - 20th International Conference, BPM 2022, Münster, Germany, September 11-16, 2022, Proceedings. (pp. 163–180). Springer.
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TSC 2024: Paper titled Discovering Work Specialization through Process Mining, currently under review.
Please navigate to the corresponding folders for more specific information.
Update 20220912: We are working on integrating this work into the OrdinoR library. Updates will follow.
Update 20250514: Restructured folders and files to hold implementations separately.
Update 20250519: The algorithms for learning execution contexts have been integrated into the recent release of OrdinoR.