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

Authors

466

  1. NT
    Nan Tang

    Tsinghua University, China

    7 publications · 440 citations

    7

    h-index

  2. MO
    Mourad Ouzzani

    Purdue University West Lafayette, United States

    6 publications · 594 citations

    6

    h-index

  3. TM
    Tova Milo

    Tel Aviv University, Israel

    5 publications · 114 citations

    5

    h-index

  4. SN
    Slava Novgorodov

    Tel Aviv University, Israel

    4 publications · 98 citations

    4

    h-index

  5. AK
    Ahmed K. Elmagarmid

    Purdue University West Lafayette, United States

    4 publications · 401 citations

    4

    h-index

1–5 of 466

Venues

  1. Proceedings of the VLDB Endowment

    PVLDB · 7 publications · 370 citations

    7

    h-index

  2. arXiv (Cornell University)

    Repository · 3 publications · 128 citations

    3

    h-index

  3. IEEE Access

    2 publications · 205 citations

    2

    h-index

  4. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 2 publications · 29 citations

    2

    h-index

  5. IEEE Transactions on Knowledge and Data Engineering

    TKDE · 2 publications · 58 citations

    2

    h-index

1–5