Monotonicity-Guided Bottom-Up Petri Net Discovery: The SPECpp Framework
Process discovery is one of the central challenges in process mining. Petri nets are particularly attractive because simple local constructs can express complex behavior, including concurrency. While their global behavior may be difficult to analyze, individual places can be efficiently characterized using monotonic properties, enabling bottom-up discovery. Unlike top-down approaches such as the Inductive Miner, which rely on predefined constructs for sequences, choices, loops, and concurrency, our approach allows such structures to emerge organically and can exploit the full expressive power of Petri nets, including free-choice constructs and long-term dependencies. The main challenge is...
| Authors | Leah Tacke genannt Unterberg, Lisa L. Mannel, Wil M. P. van der Aalst |
|---|---|
| Primary category | cs.DB |
| Published | 10 August 2026 |
| Last updated at source | 10 August 2026 |
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