Dense Document Representation
Dense Document Representation is a document-level vectorial encoding in which semantic information is embedded into a continuous, low-dimensional space through neural or statistical models, distinguishing it from sparse, high-dimensional representations by capturing contextual and syntactic nuances via distributed feature activation.
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7.6K
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133
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2017–2026
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Distributed Representations of Sentences and Documents
Quoc V. Le, Tomáš Mikolov · arXiv (Cornell University) · 2014 · 5.1K citations · Full text
Document representation and feature combination for deceptive spam review detection
Luyang Li, Bing Qin, Wenjing Ren et al. · Neurocomputing · 2017 · 154 citations
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Google (United States)
Mountain View, United States
5 h-index
19 publications
12.5K citations

Chinese Academy of Sciences
Beijing, China
3 h-index
5 publications
81 citations

University of Massachusetts Amherst
Amherst Center, United States
3 h-index
6 publications
530 citations
Microsoft Research Asia (China)
Beijing, China
2 h-index
6 publications
156 citations

University of Pisa
Pisa, Italy
2 h-index
2 publications
91 citations

University of Glasgow
Glasgow, United Kingdom
2 h-index
6 publications
273 citations
Institute of Information Engineering
Beijing, China
2 h-index
4 publications
99 citations
Microsoft Research (United Kingdom)
Cambridge, United Kingdom
2 h-index
5 publications
431 citations
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Repository · 6 publications · 5.4K citations
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