Minimum Change ≠ Best Cleaning: Parallel and Incremental Error Detection under Integrity Constraints
Summary: Shows minimum-change repairs fail when errors co-occur; uses Bayesian inference to score conflicting cells and pinpoint erroneous attribute values instead of minimal edits. Introduces provably scalable parallel conflict detection and incremental, parallel error-detection algorithms. (summarized by gpt-5-mini on Feb 11 2026)
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Authors
- 1. Jiahui Chen
- 2. Yu Sun
- 3. Shaoxu Song
- 4. Haiwei Zhang
- 5. Xiaojie Yuan
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