Short-term User Modeling
Short-Term User Modeling is a user modeling approach that captures temporally limited behavioral patterns and contextual interactions within a session or short time window to personalize search results, distinguishing it from long-term modeling by focusing on immediate, ephemeral user intent rather than stable, persistent preferences.
14
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2.1K
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59
Authors
24
Institutions
Publications per year
2017–2026
9
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Qiao Liu, Yifu Zeng, Refuoe Mokhosi et al. · 2018 · 956 citations
Neural News Recommendation with Long- and Short-term User Representations
Mingxiao An, Fangzhao Wu, Chuhan Wu et al. · 2019 · 331 citations · Full text
Adaptive User Modeling with Long and Short-Term Preferences for Personalized Recommendation
Zeping Yu, Jianxun Lian, Ahmad Mahmoody et al. · 2019 · 178 citations · Full text
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Microsoft Research Asia (China)
Beijing, China
3 h-index
6 publications
1.4K citations
Tsinghua University
Beijing, China
2 h-index
4 publications
472 citations
University of Science and Technology of China
Hefei, China
2 h-index
3 publications
706 citations
International Institute of Information Technology, Hyderabad
Hyderabad, India
1 h-index
3 publications
105 citations
University of California San Diego
San Diego, United States
1 h-index
1 publications
54 citations
Shandong University
Jinan, China
1 h-index
3 publications
345 citations

Zhejiang University
Hangzhou, China
1 h-index
7 publications
287 citations
Georgia Institute of Technology
Atlanta, United States
1 h-index
1 publications
41 citations
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1 publications · 26 citations
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1 publications · 115 citations
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Conference · 1 publications · 47 citations
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1 publications · 44 citations
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