Top-k Query Processing

Top-K Query Processing is a query processing method that belongs to the class of selective retrieval techniques, distinguished by its focus on efficiently returning only the k highest-ranked results according to a specified scoring function, without requiring the evaluation of the entire result set.

376

Publications

19.3K

Citations

769

Authors

302

Institutions

Publications per year

2017–2026

62

Authors

769

  1. XL
    Xuemin Lin

    UNSW Sydney, Australia

    19 publications · 1.2K citations

    17

    h-index

  2. WZ
    Wenjie Zhang

    UNSW Sydney, Australia

    12 publications · 739 citations

    12

    h-index

  3. KC
    Kevin Chen–Chuan Chang

    University of Illinois Urbana-Champaign, United States

    12 publications · 1.3K citations

    12

    h-index

  4. JX
    Jeffrey Xu Yu

    Chinese University of Hong Kong, Hong Kong SAR China

    11 publications · 676 citations

    11

    h-index

  5. TH
    Takahiro Hara

    The University of Osaka, Japan

    12 publications · 228 citations

    11

    h-index

1–5 of 769

Venues

  1. IEEE Transactions on Knowledge and Data Engineering

    TKDE · 39 publications · 1.5K citations

    24

    h-index

  2. Proceedings of the VLDB Endowment

    PVLDB · 32 publications · 2.1K citations

    22

    h-index

  3. The VLDB Journal

    14 publications · 1.1K citations

    14

    h-index

  4. Information Sciences

    12 publications · 336 citations

    12

    h-index

  5. ACM Transactions on Database Systems

    TODS · 13 publications · 1.2K citations

    12

    h-index

1–5