Automated Data Cleaning
Automated Data Cleaning is a data preprocessing methodology that systematically identifies, corrects, or removes inaccuracies, inconsistencies, and errors in datasets through algorithmic or rule-based procedures without substantial human intervention.
114
Publications
5.7K
Citations
466
Authors
201
Institutions
Publications per year
2017–2026
61
Parents
114
MegaDepth: Learning Single-View Depth Prediction from Internet Photos
Zhengqi Li, Noah Snavely · 2018 · 1.1K citations
Xu Chu, John Morcos, Ihab F. Ilyas et al. · 2015 · 276 citations
Discovering informative patterns and data cleaning
Isabelle Guyon, Nada Matic, Vladimir Vapnik · 1996 · 235 citations
Mohamed Yakout, Ahmed K. Elmagarmid, Jennifer Neville et al. · Proceedings of the VLDB Endowment · 2011 · 217 citations
1–5 of 114
466
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201

Tel Aviv University
Tel Aviv, Israel
6 h-index
17 publications
370 citations
Microsoft (United States)
Redmond, United States
4 h-index
6 publications
319 citations

University of Waterloo
Waterloo, Canada
4 h-index
8 publications
1K citations
Qatar Airways (Qatar)
Doha, Qatar
3 h-index
7 publications
1.3K citations
Simon Fraser University
Burnaby, Canada
3 h-index
5 publications
405 citations
Purdue University West Lafayette
West Lafayette, United States
3 h-index
4 publications
464 citations
University of California, Santa Cruz
Santa Cruz, United States
2 h-index
2 publications
65 citations

University of Edinburgh
Edinburgh, United Kingdom
2 h-index
4 publications
84 citations
1–8 of 201
PVLDB · 7 publications · 370 citations
7
h-index
Repository · 3 publications · 128 citations
3
h-index
2 publications · 205 citations
2
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Conference · 2 publications · 29 citations
2
h-index
TKDE · 2 publications · 58 citations
2
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1–5