Automatic Data Repair: Are We Ready to Deploy?
Summary: A taxonomy-driven study benchmarks 12 data-repair algorithms across 12 datasets, error conditions, and four downstream tasks using a practical error-reduction metric. A unified repair optimization strategy improves state-of-the-art methods, showing repair remains beneficial—even clean data is not the performance ceiling. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Wei Ni (City University of Hong Kong; Zhejiang University)
- 2. Xiaoye Miao (Zhejiang University)
- 3. Xiangyu Zhao (City University of Hong Kong)
- 4. Yangyang Wu (Zhejiang University)
- 5. Shuwei Liang (Zhejiang University)
- 6. Jianwei Yin (Zhejiang University)
BibTeX Citation
@article{ni_vldb24,
title = {{Automatic Data Repair: Are We Ready to Deploy?}},
author = {Ni, Wei and Miao, Xiaoye and Zhao, Xiangyu and Wu, Yangyang and Liang, Shuwei and Yin, Jianwei},
journal = {PVLDB},
series = {{VLDB} '24},
volume = {17},
number = {10},
pages = {2617--2630},
doi = {10.14778/3675034.3675051},
url = {https://doi.org/10.14778/3675034.3675051},
year = {2024}
}Incoming Citations (Sorted by Pagerank)
Showing 8 of 8 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 9,697 | Clean4TSDB: A Data Cleaning Tool for Time Series Databases | 2024 | VLDB | 5.2351259e-05 |
| 10,131 | Towards Scalable Visual Data Wrangling via Direct Manipulation | 2026 | CIDR | 5.093636e-05 |
| 10,322 | Minimum Change ≠ Best Cleaning: Parallel and Incremental Error Detection under Integrity Constraints | 2026 | SIGMOD | 5.093636e-05 |
| 10,604 | Fault Lines: Benchmarking the Impact of Label Data Quality on ML Robustness and Fairness | 2026 | VLDB | 5.093636e-05 |
| 10,932 | Federated Incomplete Tabular Data Prediction with Missing Complementarity | 2025 | VLDB | 5.093636e-05 |
| 10,966 | UniClean: A Scalable Data Cleaning Solution for Mixed Errors based on Unified Cleaners and Optimized Cleaning Workflow | 2025 | VLDB | 5.093636e-05 |
| 11,038 | DemandClean: A Multi-Objective Learning Framework for Balancing Model Tolerance to Data Authenticity and Diversity | 2025 | VLDB | 5.093636e-05 |
| 11,343 | Generalizable Data Cleaning of Tabular Data in Latent Space | 2024 | VLDB | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 36 of 36 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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| 10 | 2,981 | Towards Dependable Data Repairing with Fixing Rules | 2014 | SIGMOD |