Sequential Item Representation is an item modeling approach that characterizes items as ordered sequences of features or interactions to capture temporal or positional dependencies distinguishing it from non-sequential item representations.
10
Publications
538
Citations
38
Authors
25
Institutions
Publications per year
2017–2026
8
Parents
Publications
10
Learning Vector-Quantized Item Representation for Transferable Sequential Recommenders
Yupeng Hou, Zhankui He, Julian McAuley et al. · 2023 · 130 citations
Causal Evidence for a Privileged Working Memory State in Early Visual Cortex
Nahid Zokaei, Sanjay Manohar, Masud Husain et al. · Journal of Neuroscience · 2013 · 102 citations · Full text
1–5 of 10
Authors
38
- LL
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- GG
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- JA
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- AS
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- JP
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1–5 of 38
Institutions
25
Texas Tech University
Lubbock, United States
1 h-index
1 publications
11 citations
Hong Kong University of Science and Technology
Hong Kong, Hong Kong
1 h-index
1 publications
11 citations
University of Lausanne
Lausanne, Switzerland
1 h-index
1 publications
23 citations
Renmin University of China
Beijing, China
1 h-index
2 publications
260 citations
Rutgers, The State University of New Jersey
New Brunswick, United States
1 h-index
1 publications
11 citations
Northeastern University
Shenyang, China
1 h-index
2 publications
36 citations
Beihang University
Beijing, China
1 h-index
1 publications
51 citations
Centre National de la Recherche Scientifique
Paris, France
1 h-index
7 publications
161 citations
1–8 of 25
Venues
- IEEE Transactions on Knowledge and Data Engineering
TKDE · 1 publications · 51 citations
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- Annals of the New York Academy of Sciences
1 publications · 23 citations
1
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- ACM Transactions on Knowledge Discovery from Data
TKDD · 1 publications · 11 citations
1
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- Journal of Neuroscience
1 publications · 102 citations
1
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- arXiv (Cornell University)
Repository · 1 publications · 22 citations
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