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.
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2.7K
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107
Authors
57
Institutions
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2017–2026
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A heuristic approach to determine an appropriate number of topics in topic modeling
Weizhong Zhao, James J. Chen, Roger Perkins et al. · BMC Bioinformatics · 2015 · 393 citations · Full text
Qian Liu, Zequan Zheng, Jiabin Zheng et al. · Journal of Medical Internet Research · 2020 · 297 citations · Full text
iTopicModel: Information Network-Integrated Topic Modeling
Yizhou Sun, Jiawei Han, Jing Gao et al. · 2009 · 151 citations
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National Center for Toxicological Research, United States
2 publications · 413 citations
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University of Hong Kong
Pok Fu Lam, Hong Kong
2 h-index
2 publications
320 citations
United States Food and Drug Administration
Silver Spring, United States
2 h-index
15 publications
2.9K citations
Harvard University
Cambridge, United States
2 h-index
2 publications
320 citations
Albany State University
Albany, United States
2 h-index
2 publications
320 citations

Brigham and Women's Hospital
Boston, United States
2 h-index
2 publications
320 citations
National Center for Toxicological Research
Pine Bluff, United States
2 h-index
15 publications
2.9K citations

Imperial College London
London, United Kingdom
2 h-index
2 publications
320 citations
Queen's University
Kingston, Canada
2 h-index
5 publications
239 citations
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2 publications · 413 citations
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Repository · 2 publications · 105 citations
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2 publications · 180 citations
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1 publications · 29 citations
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1 publications · 297 citations
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