Data Disambiguation

Data Disambiguation is a data transformation technique that resolves ambiguities in datasets by identifying and distinguishing between overlapping, conflicting, or indistinguishable data instances to ensure semantic clarity and uniqueness.

41

Publications

2K

Citations

134

Authors

60

Institutions

Publications per year

2017–2026

6

Authors

134

  1. MA
    Mohammad Al Hasan

    Indiana University – Purdue University Indianapolis, United States

    3 publications · 73 citations

    3

    h-index

  2. BZ
    Baichuan Zhang

    Indiana University – Purdue University Indianapolis, United States

    3 publications · 73 citations

    3

    h-index

  3. TK
    Tanay Kumar Saha

    Indiana University – Purdue University Indianapolis, United States

    3 publications · 73 citations

    3

    h-index

  4. AH
    Alberto H. F. Laender

    Universidade Federal de Minas Gerais, Brazil

    2 publications · 114 citations

    2

    h-index

  5. JT
    James Tuck

    North Carolina State University, United States

    2 publications · 484 citations

    2

    h-index

1–5 of 134

Venues

  1. International Journal of Approximate Reasoning

    2 publications · 137 citations

    2

    h-index

  2. Scientometrics

    2 publications · 38 citations

    2

    h-index

  3. ACM SIGARCH Computer Architecture News

    1 publications · 265 citations

    1

    h-index

  4. 1

    h-index

  5. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 1 publications · 12 citations

    1

    h-index

1–5