Similarity Thresholding

Similarity Thresholding is a duplicate detection technique that classifies record pairs as duplicates or non-duplicates by comparing their similarity score against a predefined threshold, thereby distinguishing it from other methods through its reliance on a fixed cutoff criterion applied to a similarity metric.

26

Publications

1.8K

Citations

77

Authors

41

Institutions

Publications per year

2017–2026

6

Authors

77

  1. KJ
    Karianne J. Bergen

    Stanford University, United States

    3 publications · 399 citations

    3

    h-index

  2. GC
    Gregory C. Beroza

    Stanford University, United States

    3 publications · 399 citations

    3

    h-index

  3. DR
    Dhruva R. Chakrabarti

    Hewlett-Packard (United States), United States

    2 publications · 287 citations

    2

    h-index

  4. MK
    Mik Kersten

    University of British Columbia, Canada

    2 publications · 122 citations

    2

    h-index

  5. KB
    Kumud Bhandari

    Hewlett-Packard (United States), United States

    2 publications · 287 citations

    2

    h-index

1–5 of 77

Venues

  1. ACM SIGPLAN Notices

    2 publications · 78 citations

    2

    h-index

  2. Geophysical Journal International

    GJI · 1 publications · 45 citations

    1

    h-index

  3. SSRN Electronic Journal

    Repository · 1 publications · 21 citations

    1

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  4. Remote Sensing

    1 publications · 12 citations

    1

    h-index

  5. Bioinformatics

    1 publications · 21 citations

    1

    h-index

1–5