Candidate Item Selection
Candidate Item Selection is a recommendation process step that involves identifying a subset of items from the full item space which are potentially relevant to a user, distinguished by its role in filtering candidate items for further ranking or scoring within conversational recommendation systems.
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10K
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295
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142
Institutions
Publications per year
2017–2026
30
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Neural Attentive Session-based Recommendation
Jing Li, Pengjie Ren, Zhumin Chen et al. · 2017 · 1.5K citations
Development of a PROMIS item bank to measure pain interference
Dagmar Amtmann, Karon F. Cook, Mark P. Jensen et al. · Pain · 2010 · 1.2K citations
Hoyeop Lee, Jinbae Im, Seongwon Jang et al. · 2019 · 350 citations
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142
University of Washington
Seattle, United States
4 h-index
10 publications
3.8K citations

Daegu University
Daegu, South Korea
3 h-index
3 publications
141 citations
Duke University
Durham, United States
3 h-index
3 publications
1.2K citations
Kookmin University
Seoul, South Korea
3 h-index
3 publications
141 citations
Microsoft Research Asia (China)
Beijing, China
3 h-index
6 publications
191 citations
University of Science and Technology of China
Hefei, China
3 h-index
9 publications
309 citations
Hannam University
Daejeon, South Korea
3 h-index
6 publications
282 citations
Yong In University
Seoul, South Korea
3 h-index
3 publications
141 citations
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4 publications · 149 citations
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Repository · 3 publications · 107 citations
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JNH · 3 publications · 141 citations
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2 publications · 119 citations
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2 publications · 95 citations
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