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Don’t be SCAREd: Use SCalable Automatic REpairing with Maximal Likelihood and Bounded Changes

Summary: SCARE uses maximal likelihood under learned distribution to select replacements; a metric balances gain and changes. Horizontal partitioning with local-to-global aggregation enables scalable, bounded-change repairs; experiments show efficiency. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
h1d42a00fba790260
Venue
SIGMOD
Year
2013
Pagerank
0.00015114401
Overall Rank
652 | 95.62%
DOI
10.1145/2463676.2463706

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{yakout_sigmod13,
        title = {{Don’t be SCAREd: Use SCalable Automatic REpairing with Maximal Likelihood and Bounded Changes}},
        author = {Yakout, Mohamed and Berti-Équille, Laure and Elmagarmid, Ahmed K.},
        series = {{SIGMOD} '13},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/2463676.2463706},
        url = {https://dl.acm.org/doi/10.1145/2463676.2463706},
        year = {2013}
}

Incoming Citations (Sorted by Pagerank)

Showing 39 of 39 citing papers.

Rank Citing Paper Year Venue Pagerank
104 HoloClean: Holistic Data Repairs with Probabilistic Inference 2017 VLDB 0.00033676943
483 ActiveClean: Interactive Data Cleaning For Statistical Modeling 2016 VLDB 0.00017584249
1,044 Data Cleaning: Overview and Emerging Challenges 2016 SIGMOD 0.00012329478
1,098 KATARA: A Data Cleaning System Powered by Knowledge Bases and Crowdsourcing 2015 SIGMOD 0.00012031983
1,342 Baran: Effective Error Correction via a Unified Context Representation and Transfer Learning 2020 VLDB 0.00010963254
1,993 RPT: Relational Pre-trained Transformer Is Almost All You Need towards Democratizing Data Preparation 2021 VLDB 9.2348951e-05
2,054 Messing Up with BART: Error Generation for Evaluating Data-Cleaning Algorithms 2016 VLDB 9.1158071e-05
2,057 Combining Quantitative and Logical Data Cleaning 2016 VLDB 9.1086574e-05
2,372 SCODED: Statistical Constraint Oriented Data Error Detection 2020 SIGMOD 8.5575299e-05
2,424 BigDansing: A System for Big Data Cleansing 2015 SIGMOD 8.483813e-05
2,748 Uni-Detect: A Unified Approach to Automated Error Detection in Tables 2019 SIGMOD 8.0572603e-05
3,264 Automatic Data Repair: Are We Ready to Deploy? 2024 VLDB 7.4774357e-05
3,360 Cleaning Denial Constraint Violations through Relaxation 2020 SIGMOD 7.3732195e-05
4,348 Horizon: Scalable Dependency-driven Data Cleaning 2021 VLDB 6.6438522e-05
4,426 Auto-Transform: Learning-to-Transform by Patterns 2020 VLDB 6.601896e-05
4,955 Adaptive Data Augmentation for Supervised Learning over Missing Data 2021 VLDB 6.3386868e-05
5,111 Sequential Data Cleaning: A Statistical Approach 2016 SIGMOD 6.2671754e-05
5,515 KATARA: Reliable Data Cleaning with Knowledge Bases and Crowdsourcing 2015 VLDB 6.0962265e-05
5,574 Saga: A Scalable Framework for Optimizing Data Cleaning Pipelines for Machine Learning Applications 2023 SIGMOD 6.0773771e-05
5,645 Self-supervised and Interpretable Data Cleaning with Sequence Generative Adversarial Networks 2023 VLDB 6.0509471e-05
5,882 ActiveClean: An Interactive Data Cleaning Framework For Modern Machine Learning 2016 SIGMOD 5.9560519e-05
5,956 Semi-Supervised Data Cleaning with Raha and Baran 2021 CIDR 5.9329823e-05
6,148 Identifying the Extent of Completeness of Query Answers over Partially Complete Databases 2015 SIGMOD 5.8684233e-05
6,801 Intermittent Query Processing 2019 VLDB 5.6776677e-05
7,252 Akane: Perplexity-Guided Time Series Data Cleaning 2024 SIGMOD 5.5714652e-05
8,230 Sparcle: Boosting the Accuracy of Data Cleaning Systems through Spatial Awareness 2024 VLDB 5.372223e-05
9,239 Auto-Test: Learning Semantic-Domain Constraints for Unsupervised Error Detection in Tables 2025 SIGMOD 5.2032182e-05
9,382 Query-Guided Resolution in Uncertain Databases 2023 SIGMOD 5.1843659e-05
9,623 GIDCL: A Graph-Enhanced Interpretable Data Cleaning Framework with Large Language Models 2024 SIGMOD 5.1486163e-05
9,626 Interactive and Deterministic Data Cleaning: A Tossed Stone Raises a Thousand Ripples 2016 SIGMOD 5.1477881e-05
10,191 Reptile: Aggregation-level Explanations for Hierarchical Data 2022 SIGMOD 5.0628015e-05
10,275 On Saving Outliers for Better Clustering over Noisy Data 2021 SIGMOD 5.0466043e-05
10,540 Minimum Change ≠ Best Cleaning: Parallel and Incremental Error Detection under Integrity Constraints 2026 SIGMOD 4.9769913e-05
11,360 UniClean: A Scalable Data Cleaning Solution for Mixed Errors based on Unified Cleaners and Optimized Cleaning Workflow 2025 VLDB 4.9769913e-05
11,593 Win-Win: On Simultaneous Clustering and Imputing over Incomplete Data 2024 VLDB 4.9769913e-05
11,744 Splitting Tuples of Mismatched Entities 2023 SIGMOD 4.9769913e-05
12,042 LOCATER: Cleaning WiFi Connectivity Datasets for Semantic Localization 2021 VLDB 4.9769913e-05
12,343 BART in Action: Error Generation and Empirical Evaluations of Data-Cleaning Systems 2016 SIGMOD 4.9769913e-05
12,380 Cleaning Timestamps with Temporal Constraints 2016 VLDB 4.9769913e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 6 of 6 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
501 Dependencies Revisited for Improving Data Quality 2008 PODS 0.00017273167
526 Improving Data Quality: Consistency and Accuracy 2007 VLDB 0.00016879
548 ERACER: A Database Approach for Statistical Inference and Data Cleaning 2010 SIGMOD 0.00016572863
716 Guided Data Repair 2011 VLDB 0.00014546968
989 Towards Certain Fixes with Editing Rules and Master Data 2010 VLDB 0.00012647631
2,784 Interaction between Record Matching and Data Repairing 2011 SIGMOD 8.0147123e-05
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