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PIClean: A Probabilistic and Interactive Data Cleaning System

Summary: PIClean is a probabilistic, interactive data cleaning system that uses low-rank approximation to uncover cross-column relationships for joint error detection and repair. User feedback confirms or rejects probabilistic fixes, continually updating models to improve accuracy and coverage. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
5784
Venue
SIGMOD
Year
2019
Pagerank
5.6270554e-05
Overall Rank
7,387 | 49.32%
DOI
10.1145/3299869.3320214

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{yu_sigmod19,
        title = {{PIClean: A Probabilistic and Interactive Data Cleaning System}},
        author = {Yu, Zhuoran and Chu, Xu},
        series = {{SIGMOD} '19},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3299869.3320214},
        url = {https://dl.acm.org/doi/10.1145/3299869.3320214},
        year = {2019}
}

Incoming Citations (Sorted by Pagerank)

Showing 3 of 3 citing papers.

Rank Citing Paper Year Venue Pagerank
5,835 Semi-Supervised Data Cleaning with Raha and Baran 2021 CIDR 6.0720263e-05
7,104 Akane: Perplexity-Guided Time Series Data Cleaning 2024 SIGMOD 5.7020425e-05
10,500 SHoTClean: Bridging Soft and Hard Constraints for Multivariate Time Series Cleaning 2026 SIGMOD 5.093636e-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
94 Potter's Wheel: An Interactive Data Cleaning System 2001 VLDB 0.00034616103
112 HoloClean: Holistic Data Repairs with Probabilistic Inference 2017 VLDB 0.00032801121
376 Discovering Denial Constraints 2013 VLDB 0.00019677674
647 Discovering Data Quality Rules 2008 VLDB 0.00015334666
1,323 Data Cleaning: Overview and Emerging Challenges 2016 SIGMOD 0.00011152602
1,351 Detecting Data Errors: Where are we and what needs to be done? 2016 VLDB 0.00011064851
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