An Experimental Evaluation of Process Concept Drift Detection
Summary: Presents a unified public evaluation framework and repository implementing representative Process Concept Drift detectors with consolidated datasets and metrics. Benchmarking across accuracy, latency, scalability, parameter sensitivity and robustness finds no dominant method, exposing trade-offs and concrete improvement targets for algorithms and practitioners. (summarized by gpt-5-mini on Feb 09 2026)
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Authors
- 1. Jan Niklas Adams (Rheinisch-Westfaelische Technische Hochschule Aachen)
- 2. Cameron Pitsch (Rheinisch-Westfaelische Technische Hochschule Aachen)
- 3. Tobias Brockhoff (Rheinisch-Westfaelische Technische Hochschule Aachen)
- 4. Wil M.P. van der Aalst (Rheinisch-Westfaelische Technische Hochschule Aachen)
BibTeX Citation
@article{adams_vldb23,
title = {{An Experimental Evaluation of Process Concept Drift Detection}},
author = {Adams, Jan Niklas and Pitsch, Cameron and Brockhoff, Tobias and van der Aalst, Wil M.P.},
journal = {PVLDB},
series = {{VLDB} '23},
volume = {16},
number = {8},
pages = {1856--1869},
doi = {10.14778/3594512.3594517},
url = {https://doi.org/10.14778/3594512.3594517},
year = {2023}
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3,785 | Detecting Change in Data Streams | 2004 | VLDB | 7.1265312e-05 |
| 4,924 | ODIN: Automated Drift Detection and Recovery in Video Analytics | 2020 | VLDB | 6.4429959e-05 |
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