Supervised Topic Modeling

Supervised Topic Modeling is a topic modeling approach that incorporates labeled data to guide the discovery of latent thematic structures, distinguishing itself from unsupervised methods by leveraging supervision to align topics with predefined outcomes or categories.

119

Publications

8.8K

Citations

392

Authors

191

Institutions

Publications per year

2017–2026

66

Authors

392

  1. JZ
    Jun Zhu

    Tsinghua University, China

    9 publications · 707 citations

    9

    h-index

  2. EP
    Eric P. Xing

    Carnegie Mellon University, United States

    6 publications · 1.2K citations

    6

    h-index

  3. AA
    Amr Ahmed

    Carnegie Mellon University, United States

    3 publications · 534 citations

    3

    h-index

  4. JB
    Jordan Boyd‐Graber

    University of Maryland, College Park, United States

    3 publications · 314 citations

    3

    h-index

  5. YC
    Yaosen Chen

    Sichuan University, China

    2 publications · 29 citations

    2

    h-index

1–5 of 392

Venues

  1. Figshare

    Repository · 4 publications · 953 citations

    4

    h-index

  2. Social Network Analysis and Mining

    3 publications · 52 citations

    3

    h-index

  3. SSRN Electronic Journal

    Repository · 3 publications · 149 citations

    3

    h-index

  4. Journal of Biomedical Informatics

    3 publications · 131 citations

    3

    h-index

  5. arXiv (Cornell University)

    Repository · 2 publications · 1.4K citations

    2

    h-index

1–5