Cold Start Modeling
Cold Start Modeling is a user modeling approach that addresses the challenge of generating accurate predictions or recommendations for new users or items with little to no historical interaction data by leveraging auxiliary information, inherent attributes, or transferable knowledge from related domains.
242
Publications
13.4K
Citations
871
Authors
288
Institutions
Publications per year
2017–2026
121
Parents
242
A collaborative filtering approach to mitigate the new user cold start problem
Jesús Bobadilla, Fernando Ortega, Antonio Hernando et al. · Knowledge-Based Systems · 2011 · 490 citations · Full text
Computing, Data Science, Data Mining +12
Srijan Kumar, Bryan Hooi, Disha Makhija et al. · 2018 · 367 citations · Full text
Senthilselvan Natarajan, V. Subramaniyaswamy, Sivaramakrishnan Natarajan et al. · Expert Systems with Applications · 2020 · 300 citations · Full text
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288
Tianjin University
Tianjin, China
11 h-index
53 publications
3K citations
Tongji University
Shanghai, China
11 h-index
46 publications
2K citations
Jilin University
Changchun, China
7 h-index
24 publications
1.3K citations
University of California, Berkeley
Berkeley, United States
7 h-index
13 publications
385 citations

Beijing Institute of Technology
Beijing, China
6 h-index
31 publications
1K citations
University of Chinese Academy of Sciences
Beijing, China
6 h-index
10 publications
292 citations

Chinese Academy of Sciences
Beijing, China
6 h-index
21 publications
1.3K citations
Tsinghua University
Beijing, China
6 h-index
15 publications
876 citations
1–8 of 288
20 publications · 484 citations
15
h-index
11 publications · 441 citations
11
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11 publications · 579 citations
11
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JES · 9 publications · 595 citations
9
h-index
7 publications · 1.1K citations
7
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1–5