Similarity-based Querying

Similarity-Based Querying is a visual querying paradigm that retrieves data based on perceptual or feature-space resemblance to a query example, distinguished from exact or semantic matching by its reliance on graded similarity measures within a continuous similarity space.

193

Publications

10K

Citations

504

Authors

223

Institutions

Publications per year

2017–2026

23

Authors

504

  1. AJ
    Agma J. M. Traina

    Universidade de São Paulo, Brazil

    13 publications · 257 citations

    11

    h-index

  2. CT
    Caetano Traina

    Universidade de São Paulo, Brazil

    12 publications · 247 citations

    11

    h-index

  3. AO
    Alberto O. Mendelzon

    University of Toronto, Canada

    5 publications · 723 citations

    5

    h-index

  4. CX
    Chuan Xiao

    Nagoya University, Japan

    5 publications · 216 citations

    5

    h-index

  5. YN
    Yasin N. Silva

    Arizona State University, United States

    4 publications · 138 citations

    4

    h-index

1–5 of 504

Venues

  1. IEEE Transactions on Knowledge and Data Engineering

    TKDE · 12 publications · 834 citations

    11

    h-index

  2. Proceedings of the VLDB Endowment

    PVLDB · 5 publications · 152 citations

    5

    h-index

  3. 3

    h-index

  4. Data & Knowledge Engineering

    DKE · 3 publications · 113 citations

    3

    h-index

  5. arXiv (Cornell University)

    Repository · 3 publications · 57 citations

    3

    h-index

1–5