Topic Clustering
Topic Clustering is a computational method in text analysis that organizes documents into coherent groups based on semantic similarity, distinguishing itself from other clustering techniques by focusing on latent thematic structures derived from textual content.
360
Publications
17.4K
Citations
1.1K
Authors
492
Institutions
Publications per year
2017–2026
151
Variants
Thematic Clustering
Parents
360
1–5 of 360
1.1K
4
h-index
4
h-index
3
h-index
Rutgers, The State University of New Jersey, United States
3 publications · 76 citations
3
h-index
3
h-index
1–5 of 1.1K
492

Harbin Institute of Technology
Harbin, China
7 h-index
17 publications
496 citations

University of Minnesota
Minneapolis, United States
6 h-index
8 publications
2.4K citations
University of Illinois Urbana-Champaign
Urbana, United States
5 h-index
20 publications
1.1K citations

City University of Hong Kong
Hong Kong, Hong Kong
5 h-index
11 publications
668 citations

Chinese Academy of Sciences
Beijing, China
5 h-index
15 publications
1.1K citations
KU Leuven
Leuven, Belgium
5 h-index
8 publications
442 citations
Carnegie Mellon University
Pittsburgh, United States
5 h-index
13 publications
861 citations
Massachusetts Institute of Technology
Cambridge, United States
4 h-index
4 publications
319 citations
1–8 of 492
12 publications · 683 citations
12
h-index
8 publications · 214 citations
8
h-index
6 publications · 148 citations
6
h-index
4 publications · 292 citations
4
h-index
4 publications · 1.9K citations
4
h-index
1–5