Data Generalization

Data Generalization is a data transformation technique that abstracts detailed data values into higher-level, more generalized forms by suppressing or aggregating specific attributes, thereby enabling broader categorization while preserving the essential structure and semantics for analytical or computational purposes.

156

Publications

9.6K

Citations

537

Authors

208

Institutions

Publications per year

2017–2026

66

Authors

537

  1. AS
    Ashish Sabharwal

    Allen Institute, United States

    3 publications · 208 citations

    3

    h-index

  2. ML
    Michael Lebowitz

    Columbia University, United States

    2 publications · 61 citations

    2

    h-index

  3. CB
    Chandra Bhagavatula

    University of Washington, United States

    2 publications · 180 citations

    2

    h-index

  4. FR
    Fiona Ryan

    Georgia Institute of Technology, United States

    2 publications · 260 citations

    2

    h-index

  5. SP
    Scott Phoenix

    University of Padua, Italy

    2 publications · 181 citations

    2

    h-index

1–5 of 537

Venues

  1. arXiv (Cornell University)

    Repository · 22 publications · 1.3K citations

    18

    h-index

  2. Sensors

    4 publications · 130 citations

    4

    h-index

  3. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 4 publications · 137 citations

    4

    h-index

  4. 3

    h-index

  5. Network Computation in Neural Systems

    2 publications · 65 citations

    2

    h-index

1–5