Count-based Embeddings
Count-Based Embeddings is a word embedding method that derives semantic representations by constructing and factorizing a global word co-occurrence matrix to capture statistical word relationships across a corpus.
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5K
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111
Authors
55
Institutions
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2017–2026
23
Variants
Count-based Distributional SemanticsCount-based Word Representations
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Columbia University
New York, United States
3 h-index
8 publications
532 citations

University of Calgary
Calgary, Canada
2 h-index
4 publications
140 citations
Mayo Clinic in Florida
Jacksonville, United States
2 h-index
16 publications
3.3K citations
Duke University
Durham, United States
1 h-index
4 publications
112 citations

National Institute of Informatics
Tokyo, Japan
1 h-index
1 publications
12 citations

University of Pisa
Pisa, Italy
1 h-index
1 publications
45 citations
University of Michigan–Dearborn
Dearborn, United States
1 h-index
1 publications
56 citations
Tokyo University of Information Sciences
Chiba, Japan
1 h-index
3 publications
609 citations
1–8 of 55
Repository · 2 publications · 104 citations
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Repository · 1 publications · 10 citations
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1 publications · 11 citations
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1 publications · 56 citations
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1 publications · 13 citations
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