Top-n Recommendation
Top-N Recommendation is a recommendation task that, within the context of personalized information filtering, is distinguished by its objective of identifying and ranking the N most relevant items for a user, where N is a predefined positive integer.
217
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16.8K
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566
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213
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Publications per year
2017–2026
119
217
Performance of recommender algorithms on top-n recommendation tasks
Paolo Cremonesi, Yehuda Koren, Roberto Turrin · 2010 · 1.4K citations
Collaborative Denoising Auto-Encoders for Top-N Recommender Systems
Yao Wu, Christopher DuBois, Alice X. Zheng et al. · 2016 · 1K citations
SLIM: Sparse Linear Methods for Top-N Recommender Systems
Xia Ning, George Karypis · 2011 · 738 citations
Leveraging Meta-path based Context for Top- N Recommendation with A Neural Co-Attention Model
Binbin Hu, Chuan Shi, Wayne Xin Zhao et al. · 2018 · 695 citations
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University of Minnesota
Minneapolis, United States
13 h-index
25 publications
3.8K citations
Tsinghua University
Beijing, China
10 h-index
27 publications
2.2K citations

Shanghai Jiao Tong University
Shanghai, China
8 h-index
27 publications
973 citations

Beijing University of Posts and Telecommunications
Beijing, China
7 h-index
15 publications
2K citations

Hanyang University
Seoul, South Korea
7 h-index
18 publications
843 citations
Fudan University
Shanghai, China
7 h-index
10 publications
921 citations

Universidade da Coruña
A Coruña, Spain
6 h-index
12 publications
448 citations

Renmin University of China
Beijing, China
6 h-index
11 publications
1.3K citations
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Repository · 9 publications · 169 citations
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8 publications · 207 citations
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6 publications · 200 citations
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