Similarity Matrix Analysis

Similarity Matrix Analysis is a methodological framework in which pairwise textual or categorical similarities derived from card sorting or text similarity analysis are systematically organized into a matrix representation to enable the identification of clustering patterns, structural relationships, or consensus across participants or documents.

875

Publications

53.5K

Citations

2.8K

Authors

965

Institutions

Publications per year

2017–2026

291

Authors

2.8K

  1. FN
    Feiping Nie

    Northwestern Polytechnical University, China

    18 publications · 1.2K citations

    15

    h-index

  2. XL
    Xuelong Li

    Northwestern Polytechnical University, China

    13 publications · 757 citations

    12

    h-index

  3. XX
    Xin-Shun Xu

    Shandong University, China

    6 publications · 322 citations

    6

    h-index

  4. RC
    Ramon Carbó‐Dorca

    Universitat de Girona, Spain

    6 publications · 238 citations

    6

    h-index

  5. DS
    Dinggang Shen

    University of North Carolina at Chapel Hill, United States

    5 publications · 376 citations

    5

    h-index

1–5 of 2.8K

Venues

  1. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 13 publications · 790 citations

    12

    h-index

  2. IEEE Transactions on Knowledge and Data Engineering

    TKDE · 12 publications · 584 citations

    12

    h-index

  3. Nucleic Acids Research

    12 publications · 2K citations

    12

    h-index

  4. arXiv (Cornell University)

    Repository · 13 publications · 409 citations

    12

    h-index

  5. IEEE Access

    12 publications · 315 citations

    10

    h-index

1–5