Topic Number Selection

Topic Number Selection is a methodological construct within topic modeling that determines the optimal number of latent topics in a corpus by balancing model complexity and interpretability through statistical, heuristic, or domain-driven criteria.

31

Publications

2.7K

Citations

107

Authors

57

Institutions

Publications per year

2017–2026

13

Authors

107

  1. SG
    Scott Grant

    Monash University, Australia

    2 publications · 100 citations

    2

    h-index

  2. HZ
    Hongyu Zhu

    Massachusetts General Hospital, United States

    2 publications · 320 citations

    2

    h-index

  3. JJ
    James J. Chen

    National Center for Toxicological Research, United States

    2 publications · 413 citations

    2

    h-index

  4. JZ
    Jiabin Zheng

    Guangdong Academy of Medical Sciences, China

    2 publications · 320 citations

    2

    h-index

  5. QC
    Qiuyi Chen

    Harvard University, United States

    2 publications · 320 citations

    2

    h-index

1–5 of 107

Venues

  1. BMC Bioinformatics

    2 publications · 413 citations

    2

    h-index

  2. arXiv (Cornell University)

    Repository · 2 publications · 105 citations

    2

    h-index

  3. Entropy

    2 publications · 180 citations

    2

    h-index

  4. ACM Transactions on Information Systems

    1 publications · 29 citations

    1

    h-index

  5. Journal of Medical Internet Research

    1 publications · 297 citations

    1

    h-index

1–5