Matrix Factorization For Cold-start
Matrix Factorization for Cold-Start is a recommendation technique that extends traditional matrix factorization by incorporating auxiliary information or structural constraints to enable prediction for users or items with no historical interaction data.
89
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2017–2026
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Senthilselvan Natarajan, V. Subramaniyaswamy, Sivaramakrishnan Natarajan et al. · Expert Systems with Applications · 2020 · 300 citations · Full text
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Indiana University – Purdue University Indianapolis, United States
3 publications · 380 citations
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Chinese Academy of Sciences
Beijing, China
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8 publications
886 citations
Tsinghua University
Beijing, China
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12 publications
264 citations
University of Technology Sydney
Sydney, Australia
3 h-index
3 publications
350 citations
Islamic Azad University Central Tehran Branch
Tehran, Iran
3 h-index
7 publications
176 citations
University of Chinese Academy of Sciences
Beijing, China
3 h-index
8 publications
862 citations
Yahoo (United States)
Sunnyvale, United States
3 h-index
8 publications
880 citations
Laboratoire Lorrain de Recherche en Informatique et ses Applications
Nancy, France
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4 publications
79 citations

Indraprastha Institute of Information Technology Delhi
Delhi, India
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4 publications
134 citations
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TKDE · 6 publications · 749 citations
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Repository · 5 publications · 138 citations
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Conference · 3 publications · 157 citations
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