Redundancy Elimination

Redundancy Elimination is a methodological process in data management that systematically identifies and removes duplicate or superfluous data entries within a core collection to enhance data quality and efficiency while preserving informational integrity.

317

Publications

18.3K

Citations

902

Authors

361

Institutions

Publications per year

2017–2026

60

Authors

902

  1. SC
    Sun Chan

    Silicon Labs (United States), United States

    6 publications · 361 citations

    6

    h-index

  2. AA
    Aditya Akella

    University of Wisconsin–Madison, United States

    6 publications · 754 citations

    6

    h-index

  3. RG
    Rajiv Gupta

    University of California, Riverside, United States

    6 publications · 441 citations

    6

    h-index

  4. AA
    Ashok Anand

    University of Wisconsin–Madison, United States

    5 publications · 544 citations

    5

    h-index

  5. WH
    Wei‐Chung Hsu

    University of Minnesota, United States

    5 publications · 190 citations

    5

    h-index

1–5 of 902

Venues

  1. ACM SIGPLAN Notices

    15 publications · 465 citations

    13

    h-index

  2. arXiv (Cornell University)

    Repository · 5 publications · 381 citations

    5

    h-index

  3. ACM Transactions on Database Systems

    TODS · 4 publications · 251 citations

    4

    h-index

  4. IEEE Transactions on Parallel and Distributed Systems

    TPDS · 4 publications · 146 citations

    4

    h-index

  5. IFAC Proceedings Volumes

    3 publications · 129 citations

    3

    h-index

1–5