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A Robust and Accurate Approach to Detect Process Drifts from Event Streams
[article]
2021
arXiv
pre-print
Business processes are bound to evolve as a form of adaption to changes, and such changes are referred as process drifts. Current process drift detection methods perform well on clean event log data, but the performance can be tremendously affected by noises. A good process drift detection method should be accurate, fast, and robust to noises. In this paper, we propose an offline process drift detection method which identifies each newly observed behaviour as a candidate drift point and checks
arXiv:2103.10749v3
fatcat:iwchmlazxbcd3o5av6fy7dxtra