Similarity Inference

Similarity Inference is a computational method that identifies and quantifies the degree of overlap or correspondence between textual, structural, or semantic elements of two or more academic artifacts to determine whether such resemblance constitutes evidence of potential intellectual dependence or originality.

85

Publications

5.6K

Citations

246

Authors

134

Institutions

Publications per year

2017–2026

28

Authors

246

  1. RD
    Rémi Denise

    APC Microbiome Institute, Ireland

    2 publications · 77 citations

    2

    h-index

  2. ME
    Michael Erdmann

    Carnegie Mellon University, United States

    2 publications · 25 citations

    2

    h-index

  3. AA
    Aniket Anand Deshmukh

    University of Michigan, United States

    2 publications · 58 citations

    2

    h-index

  4. TS
    Thomas Sicheritz‐Pontén

    Technical University of Denmark, Denmark

    2 publications · 77 citations

    2

    h-index

  5. ML
    Maria Lestido

    Ecogenomics (Japan), Japan

    2 publications · 77 citations

    2

    h-index

1–5 of 246

Venues

  1. arXiv (Cornell University)

    Repository · 3 publications · 168 citations

    3

    h-index

  2. Journal of Computational Biology

    2 publications · 239 citations

    2

    h-index

  3. PLoS Computational Biology

    2 publications · 874 citations

    2

    h-index

  4. Hereditas

    2 publications · 100 citations

    2

    h-index

  5. Bioinformatics

    2 publications · 42 citations

    2

    h-index

1–5