Synthetic Event Logs for Concept Drift Detection

Citation Author(s):
Victor
Gallego-Fontenla
Universidade de Santiago de Compostela
Submitted by:
Victor Gallego-...
Last updated:
Tue, 05/17/2022 - 22:21
DOI:
10.21227/fyrn-4553
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License:
Creative Commons Attribution
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Abstract 

Real life business processes change over time, in both planned and unexpected ways. These changes over time are called concept drifts and its detection is a big challenge in process mining since the inherent complexity of the data makes difficult distinguishing between a change and an anomalous execution. The following logs were generated synthetically in order to prove the quality of different concept drift detection algorithms.

Instructions: 

The log files are available in 4 different sizes: 2500, 5000, 7500 and 10000 traces.

Each log has a sudden drift at every 10% of the log.

The change patterns applied to the model are the ones from the paper "Change patterns and change support features - Enhancing flexibility in process-aware information systems".

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