Abstract
The discovery of process models from event logs has been a well-understood topic regarding activity-centric processes. For alternative paradigms (e.g., data- or object-centric processes as implemented in many information systems), however, this model discovery still poses several challenges. One of these challenges concerns the discovery of object behavior expressed in terms of object lifecycle processes. In particular, this discovery requires the consideration of different granularity levels (i.e., object states and object attributes). This paper presents an approach for discovering object lifecycle processes. The approach divides the discovery of object lifecycle processes into subproblems by preprocessing event logs to enable the use of well-known discovery algorithms. Overall, object-centric process mining gives insights into data-driven and object-centric processes as implemented in many information systems.
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Notes
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Using the following thresholds: Dependency (0.5), AND (0.65), Loop 2 (0.5).
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Breitmayer, M., Arnold, L., Goth, D., Reichert, M. (2024). An Approach for Discovering Data-Driven Object Lifecycle Processes. In: Araújo, J., de la Vara, J.L., Santos, M.Y., Assar, S. (eds) Research Challenges in Information Science. RCIS 2024. Lecture Notes in Business Information Processing, vol 513. Springer, Cham. https://doi.org/10.1007/978-3-031-59465-6_15
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