Sparse Document Representation
Sparse Document Representation is a document representation method in which a document is encoded using a high-dimensional vector space wherein most features are zero, thereby emphasizing a small subset of salient terms or indices to distinguish documents within a corpus.
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6.5K
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2017–2026
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Buğra Gedik, Henrique Andrade, Kun‐Lung Wu et al. · 2008 · 422 citations
Proximal Methods for Sparse Hierarchical Dictionary Learning
Rodolphe Jenatton, Julien Mairal, Francis R. Bach et al. · Food Chemistry · 2010 · 331 citations
Text Mining using Non-Negative Matrix Factorizations
V. Paúl Pauca, Farial Shahnaz, Michael W. Berry et al. · 2004 · 310 citations
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Peking University
Beijing, China
3 h-index
7 publications
255 citations
Google (United States)
Mountain View, United States
3 h-index
12 publications
2.2K citations
Massachusetts Institute of Technology
Cambridge, United States
3 h-index
7 publications
582 citations
University of Illinois Urbana-Champaign
Urbana, United States
3 h-index
5 publications
159 citations
Beijing Jiaotong University
Beijing, China
3 h-index
10 publications
856 citations
Wuhan University
Wuhan, China
3 h-index
9 publications
294 citations
Chinese University of Hong Kong
Hong Kong, Hong Kong
2 h-index
6 publications
384 citations
Fudan University
Shanghai, China
2 h-index
3 publications
166 citations
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Repository · 5 publications · 195 citations
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Conference · 3 publications · 146 citations
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MPE · 2 publications · 35 citations
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TKDE · 2 publications · 81 citations
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2 publications · 60 citations
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