ERACER: A Database Approach for Statistical Inference and Data Cleaning
Summary: ERACER is a framework that infers missing values and cleans errors via belief propagation on relational networks, implementable in SQL/UDFs. Uses shrinkage to cleanse dirty data and handles cyclic dependencies, achieving Bayesian accuracy with approximate inference on synthetic data. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Chris Mayfield (Purdue University)
- 2. Jennifer Neville (Purdue University)
- 3. Sunil Prabhakar (Purdue University)
BibTeX Citation
@inproceedings{mayfield_sigmod10,
title = {{ERACER: A Database Approach for Statistical Inference and Data Cleaning}},
author = {Mayfield, Chris and Neville, Jennifer and Prabhakar, Sunil},
series = {{SIGMOD} '10},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/1807167.1807178},
url = {https://dl.acm.org/doi/10.1145/1807167.1807178},
year = {2010}
}
Incoming Citations (Sorted by Pagerank)
Showing 32 of 32 citing papers.
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Outgoing Citations (Sorted by Pagerank)
Showing 5 of 5 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 155 | MAD Skills: New Analysis Practices for Big Data | 2009 | VLDB | 0.00028713176 |
| 185 | A Cost-Based Model and Effective Heuristic for Repairing Constraints by Value Modification | 2005 | SIGMOD | 0.00026231189 |
| 533 | Improving Data Quality: Consistency and Accuracy | 2007 | VLDB | 0.0001705859 |
| 1,437 | Querying Continuous Functions in a Database System | 2008 | SIGMOD | 0.00010790718 |
| 2,365 | A Revival of Integrity Constraints for Data Cleaning | 2008 | VLDB | 8.6867205e-05 |
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