Knowledge-based Recommendation Systems
Knowledge-Based Recommendation Systems is a recommender system that specifically relies on explicit domain knowledge and user preferences to generate recommendations by reasoning about the functional or physical characteristics of items, distinguishing it from collaborative or content-based approaches through its emphasis on knowledge representation and inference.
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Publications
29.1K
Citations
1.7K
Authors
565
Institutions
Publications per year
2017–2026
308
505
Xiang Wang, Xiangnan He, Yixin Cao et al. · 2019 · 2.1K citations · Full text
Recommender system application developments: A survey
Jie Lü, Dianshuang Wu, Mingsong Mao et al. · Decision Support Systems · 2015 · 1.6K citations
Knowledge Graph Convolutional Networks for Recommender Systems
2019 · 967 citations · Full text
A Survey on Knowledge Graph-Based Recommender Systems
Qingyu Guo, Fuzhen Zhuang, Chuan Qin et al. · IEEE Transactions on Knowledge and Data Engineering · 2020 · 845 citations · Full text
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University of Klagenfurt
Klagenfurt, Austria
15 h-index
34 publications
2.1K citations

Chinese Academy of Sciences
Beijing, China
12 h-index
24 publications
3.5K citations
Graz University of Technology
Graz, Austria
10 h-index
31 publications
1.4K citations
Tsinghua University
Beijing, China
10 h-index
27 publications
3.2K citations
University of Bari Aldo Moro
Bari, Italy
10 h-index
35 publications
1.2K citations

Shanghai Jiao Tong University
Shanghai, China
10 h-index
21 publications
950 citations
University of Science and Technology of China
Hefei, China
9 h-index
18 publications
3.9K citations
University of Chinese Academy of Sciences
Beijing, China
9 h-index
24 publications
2.6K citations
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35 publications · 2.5K citations
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19 publications · 1.1K citations
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16 publications · 590 citations
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10 publications · 586 citations
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TKDE · 11 publications · 1.4K citations
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