Co-occurrence Matrix Factorization
Co-Occurrence Matrix Factorization is a dimensionality reduction technique in natural language processing that factorizes a term-context co-occurrence matrix into lower-dimensional vector representations to capture semantic relationships between words based on their distributional properties.
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42.2K
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2017–2026
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quanteda: An R package for the quantitative analysis of textual data
Kenneth Benoit, Kohei Watanabe, H. P. Wang et al. · The Journal of Open Source Software · 2018 · 1.3K citations · Full text
Data clustering using evidence accumulation
Ana Fred, Anil K. Jain · 2003 · 516 citations
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Harbin Institute of Technology
Harbin, China
4 h-index
11 publications
422 citations
Wuhan University
Wuhan, China
3 h-index
7 publications
792 citations
Université Paris Cité
Paris, France
3 h-index
5 publications
123 citations
Institut national de recherche en sciences et technologies du numérique
Le Chesnay-Rocquencourt, France
2 h-index
2 publications
64 citations

Délégation Paris 5
Paris, France
2 h-index
3 publications
91 citations

Chinese Academy of Sciences
Beijing, China
2 h-index
9 publications
98 citations
Stanford University
Stanford, United States
2 h-index
4 publications
68K citations

University of Edinburgh
Edinburgh, United Kingdom
2 h-index
4 publications
275 citations
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Repository · 3 publications · 168 citations
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BRM · 2 publications · 1.1K citations
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