Semantic Similarity Visualization

Semantic Similarity Visualization is a visual representation method that encodes the degree of conceptual relatedness between semantic entities within a network structure, distinguishing itself by explicitly mapping similarity metrics derived from semantic models into spatial, geometric, or graphical attributes to facilitate interpretability and analysis.

27

Publications

1.6K

Citations

98

Authors

52

Institutions

Publications per year

2017–2026

13

Authors

98

  1. FY
    Fangtian Ying

    Zhejiang University, China

    2 publications · 141 citations

    2

    h-index

  2. CZ
    Chao Zhang

    Zhejiang University, China

    2 publications · 141 citations

    2

    h-index

  3. LL
    Lijuan Liu

    Shandong First Medical University, China

    2 publications · 141 citations

    2

    h-index

  4. CY
    Cheng Yao

    Zhejiang University, China

    2 publications · 141 citations

    2

    h-index

  5. RT
    Richard T. Serpe

    Kent State University, United States

    1 publications · 40 citations

    1

    h-index

1–5 of 98

Venues

  1. BioData Mining

    2 publications · 272 citations

    2

    h-index

  2. IEEE Transactions on Neural Networks

    1 publications · 29 citations

    1

    h-index

  3. Proceedings of the National Academy of Sciences

    PNAS · 1 publications · 147 citations

    1

    h-index

  4. Bioinformatics

    1 publications · 86 citations

    1

    h-index

  5. Data and Information Management

    1 publications · 27 citations

    1

    h-index

1–5