Knowledge-based Recommendation
Knowledge-Based Recommendation is a type of recommender system that generates suggestions by leveraging structured domain knowledge and explicit user preferences, distinguishing itself from other recommendation approaches through its reliance on inference mechanisms rather than historical or collaborative data patterns.
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Publications per year
2017–2026
932
Variants
Knowledge-based Recommender Systems
Parents
1.4K
Xiang Wang, Xiangnan He, Yixin Cao et al. · 2019 · 2.1K citations · Full text
Collaborative Knowledge Base Embedding for Recommender Systems
Fuzheng Zhang, Nicholas Jing Yuan, Defu Lian et al. · 2016 · 1.8K citations
Hongwei Wang, Fuzheng Zhang, Xing Xie et al. · 2018 · 1K citations · Full text
Knowledge Graph Convolutional Networks for Recommender Systems
2019 · 967 citations · Full text
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Chinese Academy of Sciences
Beijing, China
25 h-index
73 publications
6.2K citations
Microsoft Research Asia (China)
Beijing, China
24 h-index
66 publications
17.4K citations
Tsinghua University
Beijing, China
24 h-index
97 publications
8.9K citations
University of Science and Technology of China
Hefei, China
22 h-index
73 publications
8.3K citations
University of Technology Sydney
Sydney, Australia
21 h-index
51 publications
3K citations

Shanghai Jiao Tong University
Shanghai, China
20 h-index
67 publications
8.2K citations

Zhejiang University
Hangzhou, China
18 h-index
80 publications
5.2K citations
Nanyang Technological University
Singapore, Singapore
18 h-index
38 publications
2.7K citations
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76 publications · 5.3K citations
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45 publications · 2.7K citations
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TKDE · 29 publications · 2.9K citations
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27 publications · 1.2K citations
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29 publications · 1.2K citations
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