Personalized Sequential Recommendation is a recommendation paradigm that, as an extension of sequential recommendation, incorporates user-specific behavioral patterns and preferences to model individualized temporal dynamics in item sequences.
51
Publications
5.3K
Citations
202
Authors
69
Institutions
Publications per year
2017–2026
40
Parents
Publications
51
Translation-based Recommendation
Ruining He, Wang-Cheng Kang, Julian McAuley · 2017 · 429 citations · Full text
SSE-PT: Sequential Recommendation Via Personalized Transformer
Liwei Wu, Shuqing Li, Cho‐Jui Hsieh et al. · 2020 · 248 citations · Full text
1–5 of 51
Authors
202
- JM
4
h-index
- RH
4
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- EC
3
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- WP
3
h-index
- MH
3
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1–5 of 202
Institutions
69
Shenzhen University
Shenzhen, China
4 h-index
14 publications
296 citations
University of California San Diego
San Diego, United States
3 h-index
8 publications
2.8K citations
Wuhan University
Wuhan, China
3 h-index
8 publications
251 citations
Macquarie University
Sydney, Australia
2 h-index
5 publications
275 citations
Zhejiang University
Hangzhou, China
2 h-index
7 publications
272 citations
Tsinghua University
Beijing, China
2 h-index
9 publications
249 citations
University of California, Los Angeles
Los Angeles, United States
2 h-index
2 publications
419 citations
Institute of Computing Technology
Beijing, China
2 h-index
7 publications
191 citations
1–8 of 69
Venues
- IEEE Access
3 publications · 138 citations
3
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- Information Processing & Management
2 publications · 67 citations
2
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- Knowledge-Based Systems
2 publications · 50 citations
2
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- IEEE Transactions on Knowledge and Data Engineering
TKDE · 2 publications · 90 citations
2
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- Expert Systems with Applications
2 publications · 55 citations
2
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1–5