Graph-based Text Clustering
Graph-Based Text Clustering is a text clustering approach that models documents and their relationships as a graph structure, where nodes represent documents or textual units and edges encode semantic or similarity relations, and applies graph partitioning or community detection algorithms to identify clusters.
106
Publications
6.5K
Citations
293
Authors
161
Institutions
Publications per year
2017–2026
24
Parents
106
Chris Biemann · 2006 · 315 citations · Full text
Bipartite graph partitioning and data clustering
Hongyuan Zha, Xiaofeng He, Chris Ding et al. · 2001 · 286 citations
Automated duplicate detection for bug tracking systems
Nicholas Jalbert, Westley Weimer · 2008 · 278 citations
1–5 of 106
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Indian Institute of Engineering Science and Technology, Shibpur, India
3 publications · 116 citations
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1–5 of 293
161
University of Illinois Chicago
Chicago, United States
3 h-index
3 publications
225 citations
Indian Institute of Engineering Science and Technology, Shibpur
Howrah, India
3 h-index
6 publications
232 citations
University of California, Berkeley
Berkeley, United States
3 h-index
3 publications
469 citations

Délégation Paris 5
Paris, France
3 h-index
8 publications
338 citations
Université Paris Cité
Paris, France
3 h-index
8 publications
338 citations
University of Illinois Urbana-Champaign
Urbana, United States
3 h-index
9 publications
1.2K citations

Huazhong University of Science and Technology
Wuhan, China
3 h-index
8 publications
341 citations
Lanzhou University
Lanzhou, China
2 h-index
5 publications
140 citations
1–8 of 161
2 publications · 33 citations
2
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2 publications · 205 citations
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2 publications · 78 citations
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TKDD · 2 publications · 203 citations
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TKDE · 2 publications · 446 citations
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1–5