Data Uniqueness Analysis

Data Uniqueness Analysis is a data profiling technique that identifies and evaluates the degree to which data values within a dataset are distinct, thereby determining the absence of duplicates and assessing the singularity of records across attributes.

11

Publications

984

Citations

30

Authors

27

Institutions

Publications per year

2017–2026

5

Authors

30

  1. TJ
    Taeho Jung

    Illinois Institute of Technology, United States

    2 publications · 107 citations

    2

    h-index

  2. JH
    Jiahui Hou

    Illinois Institute of Technology, United States

    2 publications · 107 citations

    2

    h-index

  3. JQ
    Jianwei Qian

    Illinois Institute of Technology, United States

    2 publications · 107 citations

    2

    h-index

  4. LC
    Linlin Chen

    University of Science and Technology of China, China

    2 publications · 107 citations

    2

    h-index

  5. JH
    Junze Han

    Illinois Institute of Technology, United States

    2 publications · 107 citations

    2

    h-index

1–5 of 30

Venues

  1. IEEE Transactions on Signal Processing

    2 publications · 26 citations

    2

    h-index

  2. Science & Justice

    1 publications · 53 citations

    1

    h-index

  3. Proceedings of the VLDB Endowment

    PVLDB · 1 publications · 24 citations

    1

    h-index

  4. SIAM Journal on Scientific Computing

    1 publications · 18 citations

    1

    h-index

  5. Analytica Chimica Acta

    1 publications · 54 citations

    1

    h-index

1–5