Proximity Data Structures

Proximity Data Structures is a geometric data structure designed to organize spatial data in a way that enables efficient query and retrieval of geometric objects based on their relative closeness or distance relationships in metric space.

74

Publications

5.8K

Citations

131

Authors

78

Institutions

Publications per year

2017–2026

6

Variants

Spatial Proximity Data Structures

Authors

131

  1. PI
    Piotr Indyk

    Massachusetts Institute of Technology, United States

    4 publications · 165 citations

    4

    h-index

  2. AC
    Antonio Corral

    University of Almería, Spain

    3 publications · 384 citations

    3

    h-index

  3. AN
    Assaf Naor

    Courant Institute of Mathematical Sciences, United States

    3 publications · 147 citations

    3

    h-index

  4. HS
    Hanan Samet

    University of Maryland, College Park, United States

    3 publications · 87 citations

    3

    h-index

  5. AA
    Alexandr Andoni

    Microsoft (United States), United States

    2 publications · 74 citations

    2

    h-index

1–5 of 131

Venues

  1. Pattern Recognition Letters

    3 publications · 345 citations

    3

    h-index

  2. Symposium on Discrete Algorithms

    Conference · 2 publications · 56 citations

    2

    h-index

  3. Psychometrika

    2 publications · 180 citations

    2

    h-index

  4. Algorithmica

    2 publications · 42 citations

    2

    h-index

  5. 2

    h-index

1–5