Deep Collaborative Filtering
Deep Collaborative Filtering is a machine learning approach within collaborative filtering that integrates deep neural networks to model complex user-item interactions by jointly learning latent representations from raw input features and interaction data.
285
Publications
27.7K
Citations
974
Authors
354
Institutions
Publications per year
2017–2026
262
Parents
285
Neural Collaborative Filtering
Xiangnan He, Lizi Liao, Hanwang Zhang et al. · 2017 · 6.6K citations · Full text
Neural Graph Collaborative Filtering
2019 · 3K citations · Full text
Suvash Sedhain, Aditya Krishna Menon, Scott Sanner et al. · 2015 · 1.2K citations
Graph Convolutional Matrix Completion
Rianne van den Berg, Thomas Kipf, Max Welling · arXiv (Cornell University) · 2017 · 1.1K citations · Full text
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354
Tsinghua University
Beijing, China
10 h-index
22 publications
3.1K citations
National University of Singapore
Singapore, Singapore
8 h-index
13 publications
21.7K citations

University of Electronic Science and Technology of China
Chengdu, China
8 h-index
19 publications
1.6K citations

Chinese Academy of Sciences
Beijing, China
8 h-index
11 publications
651 citations
Tencent (China)
Shenzhen, China
7 h-index
8 publications
279 citations

Sun Yat-sen University
Guangzhou, China
6 h-index
19 publications
1.4K citations

Beijing University of Posts and Telecommunications
Beijing, China
6 h-index
21 publications
2.6K citations
Shandong University
Jinan, China
6 h-index
16 publications
7.1K citations
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20 publications · 1.1K citations
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Repository · 17 publications · 2.1K citations
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8 publications · 1.1K citations
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Conference · 7 publications · 707 citations
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6 publications · 311 citations
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