A Conformance Checking-based Approach for Sudden Drift Detection in Business Processes

Real life business processes change over time, in both planned and unexpected ways. The detection of these changes is crucial for organizations to ensure that the expected real behavior are as similar possible. These time called concept drift its a big challenge process mining since inherent complexity data makes difficult distinguishing between an anomalous execution. In this paper, we present C2D2 (Conformance Checking-based Drift Detection), new approach detect sudden control-flow models from event traces. combines discovery techniques with conformance checking methods perform offline detection. Our has been validated synthetic benchmarking dataset formed by 68 logs, showing improvement accuracy while maintaining minimum delay