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Event Logs and Process Models for Evaluating Discovery Algorithm Robustness under Noise

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IEEE2026-04-17 收录
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https://ieee-dataport.org/documents/event-logs-and-process-models-evaluating-discovery-algorithm-robustness-under-noise
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This dataset contains clean and noisy versions of real-life event logs, along with process models discovered using Alpha Miner, Heuristics Miner, and Inductive Miner. Noise was injected at varying levels and types using the SNIP tool to evaluate the robustness and stability of process discovery algorithms. It enables reproducible experiments on the impact of data quality on process mining outcomes.
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Anandi Karunaratne
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