Probabilistic Text Clustering is a text clustering paradigm that models document groupings through probabilistic frameworks by representing documents as random samples from latent generative distributions, thereby distinguishing itself from heuristic or distance-based methods through explicit statistical assumptions about textual data formation.
70
Publications
6.1K
Citations
188
Authors
113
Institutions
Publications per year
2017–2026
10
Parents
Publications
70
Identifying topical authorities in microblogs
Aditya Pal, Scott Counts · 2011 · 350 citations
Clustering scientific documents with topic modeling
Chyi-Kwei Yau, Alan L. Porter, Nils C. Newman et al. · Scientometrics · 2014 · 238 citations
1–5 of 70
Authors
188
- PS
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- MS
2
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- DK
2
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- CC
2
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1–5 of 188
Institutions
113
University of Illinois Chicago
Chicago, United States
4 h-index
5 publications
309 citations
University of Illinois Urbana-Champaign
Urbana, United States
3 h-index
9 publications
824 citations
Florida International University
Miami, United States
2 h-index
5 publications
151 citations
University of Cambridge
Cambridge, United Kingdom
2 h-index
3 publications
83 citations
University of Milano-Bicocca
Milan, Italy
2 h-index
5 publications
79 citations
Carnegie Mellon University
Pittsburgh, United States
2 h-index
4 publications
408 citations
Stanford University
Stanford, United States
2 h-index
4 publications
122 citations
Tsinghua University
Beijing, China
2 h-index
2 publications
31 citations
1–8 of 113
Venues
- Information Processing & Management
4 publications · 173 citations
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- ACM Transactions on Knowledge Discovery from Data
TKDD · 2 publications · 203 citations
2
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- IEEE Transactions on Knowledge and Data Engineering
TKDE · 2 publications · 54 citations
2
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- The Florida AI Research Society
Conference · 1 publications · 26 citations
1
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- IEEE Transactions on Pattern Analysis and Machine Intelligence
TPAMI · 1 publications · 60 citations
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