Systematic Development of Data Mining-Based Data Quality Tools
Summary: Introduces a test generator that systematically creates and pollutes benchmark databases to calibrate data-quality error measures when legacy schemas and constraints are unreliable. Integrated with C4.5-based auditing, it complements scrubbing in a DaimlerChrysler case study. (summarized by gpt-5.6-luna on Jul 24 2026)
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Authors
- 1. Dominik Luebbers (RWTH Aachen University)
- 2. Udo Grimmer (DaimlerChrysler AG)
- 3. Matthias Jarke (Fraunhofer Institute; RWTH Aachen University)
BibTeX Citation
@article{luebbers_vldb03,
title = {{Systematic Development of Data Mining-Based Data Quality Tools}},
author = {Luebbers, Dominik and Grimmer, Udo and Jarke, Matthias},
journal = {PVLDB},
series = {{VLDB} '03},
doi = {10.1016/B978-012722442-8/50055-0},
url = {https://doi.org/10.1016/B978-012722442-8/50055-0},
year = {2003}
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Outgoing Citations (Sorted by Pagerank)
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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 |
|---|---|---|---|---|
| 58 | The Merge/Purge Problem for Large Databases | 1995 | SIGMOD | 0.00040116748 |
| 142 | LOF: Identifying Density-Based Local Outliers | 2000 | SIGMOD | 0.0002962566 |
| 751 | AJAX: An Extensible Data Cleaning Tool | 2000 | SIGMOD | 0.00014369237 |
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