Multi-dimensional Range Searching

Multi-Dimensional Range Searching is a computational problem in computational geometry and database theory that involves retrieving all points in a multi-dimensional space satisfying a given range query, distinguished from one-dimensional range searching by its handling of simultaneous constraints across two or more dimensions.

83

Publications

6.7K

Citations

225

Authors

114

Institutions

Publications per year

2017–2026

11

Authors

225

  1. CC
    Chung‐Min Chen

    University of Wisconsin–Milwaukee, United States

    4 publications · 73 citations

    4

    h-index

  2. WH
    Wei Hong

    University of California, Berkeley, United States

    3 publications · 434 citations

    3

    h-index

  3. SP
    Sunil Prabhakar

    Purdue University West Lafayette, United States

    3 publications · 348 citations

    3

    h-index

  4. RG
    Ramesh Govindan

    University of Southern California, United States

    3 publications · 434 citations

    3

    h-index

  5. ZW
    Zongda Wu

    Shaoxing University, China

    2 publications · 68 citations

    2

    h-index

1–5 of 225

Venues

  1. IEEE Transactions on Knowledge and Data Engineering

    TKDE · 4 publications · 104 citations

    4

    h-index

  2. ACM Transactions on Database Systems

    TODS · 3 publications · 510 citations

    3

    h-index

  3. Journal of the ACM

    JACM · 2 publications · 196 citations

    2

    h-index

  4. Information Systems

    2 publications · 36 citations

    2

    h-index

  5. Future Generation Computer Systems

    FGCS · 2 publications · 43 citations

    2

    h-index

1–5