Topic-based Document Clustering
Topic-Based Document Clustering is a document clustering approach that organizes documents into groups based on shared thematic content derived from latent topics, distinguishing itself from other clustering methods by explicitly leveraging topic models to represent and cluster documents according to their semantic themes.
111
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6.5K
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318
Authors
148
Institutions
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2017–2026
46
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111
Document clustering based on non-negative matrix factorization
Wei Xu, Xin Liu, Yihong Gong · 2003 · 1.9K citations
Document clustering: TF-IDF approach
Prafulla Bafna, Dhanya Pramod, Anagha Vaidya · 2016 · 266 citations
Clustering scientific documents with topic modeling
Chyi-Kwei Yau, Alan L. Porter, Nils C. Newman et al. · Scientometrics · 2014 · 238 citations
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148

University of Minnesota
Minneapolis, United States
3 h-index
3 publications
215 citations
KU Leuven
Leuven, Belgium
3 h-index
6 publications
350 citations
University of Florida
Gainesville, United States
3 h-index
4 publications
428 citations

Beijing University of Posts and Telecommunications
Beijing, China
3 h-index
7 publications
206 citations
Tsinghua University
Beijing, China
2 h-index
5 publications
51 citations
Stanford University
Stanford, United States
2 h-index
5 publications
206 citations
University of Technology Sydney
Sydney, Australia
2 h-index
6 publications
1.3K citations
Rutgers, The State University of New Jersey
New Brunswick, United States
2 h-index
3 publications
75 citations
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4 publications · 411 citations
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3 publications · 64 citations
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2 publications · 85 citations
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IJCC · 2 publications · 30 citations
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1 publications · 56 citations
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