Spatial Query Optimization

Spatial Query Optimization is a methodological framework within spatial databases that systematically enhances the efficiency of spatial query processing by minimizing computational and I/O costs through the selection of optimal execution plans based on spatial data characteristics and indexing structures.

128

Publications

5.9K

Citations

376

Authors

157

Institutions

Publications per year

2017–2026

31

Authors

376

  1. NM
    Nikos Mamoulis

    University of Hong Kong, Hong Kong SAR China

    11 publications · 710 citations

    11

    h-index

  2. DP
    Dimitris Papadias

    Hong Kong University of Science and Technology, Hong Kong SAR China

    9 publications · 1.1K citations

    9

    h-index

  3. WL
    Wang-Chien Lee

    Pennsylvania State University, United States

    5 publications · 335 citations

    5

    h-index

  4. ML
    Man Lung Yiu

    Hong Kong Polytechnic University, Hong Kong SAR China

    5 publications · 449 citations

    5

    h-index

  5. DL
    Dik Lun Lee

    Hong Kong University of Science and Technology, Hong Kong SAR China

    4 publications · 695 citations

    4

    h-index

1–5 of 376

Venues

  1. IEEE Transactions on Knowledge and Data Engineering

    TKDE · 12 publications · 542 citations

    12

    h-index

  2. GeoInformatica

    4 publications · 125 citations

    4

    h-index

  3. Proceedings of the VLDB Endowment

    PVLDB · 4 publications · 95 citations

    4

    h-index

  4. ACM SIGMOD Record

    3 publications · 212 citations

    3

    h-index

  5. The VLDB Journal

    3 publications · 168 citations

    3

    h-index

1–5