Automated Discovery of Structured Process Models From Event Logs: The Discover-and-Structure Approach
A Augusto, R Conforti, M Dumas, M La Rosa, G Bruno
Data & Knowledge Engineering | Elsevier | Published : 2018
This article tackles the problem of discovering a process model from an event log recording the execution of tasks in a business process. Previous approaches to this reverse-engineering problem strike different tradeoffs between the accuracy of the discovered models and their structural complexity. With respect to the latter property, empirical studies have demonstrated that block-structured process models are gener- ally more understandable and less error-prone than unstructured ones. Accordingly, several methods for automated process model discovery generate block-structured models only. These methods however intertwine the objective of producing accurate models with that of ensuring their..View full abstract
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Awarded by Australian Research Council
Awarded by Estonian Research Council
This research is partly funded by the Australian Research Council (grant DP150103356) and the Estonian Research Council (grant IUT20-55).