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Graph Convolution Network (GCN) has attracted significant attention and become the most popular method for learning graph representations.
Item-based collaborative filtering recommendation algorithms
Joseph A. Konstan Badrul Munir Sarwar, George Karypis and John Riedl. 2001 · 2001
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Factorization meets the neighborhood: a multifaceted collaborative filtering model
Yehuda Koren. 2008 · 2008
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Matrix Factorization Techniques for Recommender Systems
Volinsky C Koren Y, Bell R. 2009 · 2009
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BPR: Bayesian Personalized Ranking from Implicit Feedback
Zeno Gantner Steffen Rendle, Christoph Freudenthaler and Lars Schmidt-Thieme. 2009 · 2009
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A Survey of Collaborative Filtering Techniques
Xiaoyuan Su and Taghi M Khoshgoftaar. 2009 · 2009
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Novel Boosting Frameworks to Improve the Performance of Collaborative Filtering
Xiaotian Jiang, Zhendong Niu, Jiamin Guo, Ghulam Mustafa, Zihan Lin, Baomi Chen, and Qian Zhou. 2013 · 2013
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HOSLIM: Higher-Order Sparse LInear Method for Top-N Recommender Systems
Evangelia Christakopoulou and George Karypis. 2014 · 2014
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Adam: A Method for Stochastic Optimization
Diederik P. Kingma and Jimmy Ba. 2015 · 2015
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Modeling User Exposure in Recommendation
James McInerney Dawen Liang, Laurent Charlin and David M. Blei. 2016 · 2016
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Ups and downs:Modeling the visual evolution of fashion trends with one-class collaborative filtering
Ruining He and Julian McAuley. 2016a · 2016
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VBPR: Visual bayesian personalized ranking from implicit feedback
Ruining He and Julian McAuley. 2016b · 2016
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Causal Embeddings for Recommendation
Jay Adams Paul Covington and Emre Sargin. 2016 · 2016
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Attention Is All You Need
Niki Parmar Jakob Uszkoreit Llion Jones Aidan N. Gomez Lukasz Kaiser Ashish Vaswani, Noam Shazeer and Illia Polosukhin. 2017 · 2017
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Development of a music recommendation system for motivating exercise. 83–86
Jiakun Fang, David Grunberg, Simon Lui, and Ye Wang. 2017 · 2017
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Attentive collaborative filtering: Multimedia recommendation with item- and component-level attention
X. He L. Nie W. Liu J. Chen, H. Zhang and T.-S. Chua. 2017 · 2017
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Semi-Supervised Classification with Graph Convolutional Networks
Thomas N. Kipf and Max Welling. 2017 · 2017
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Graph Convolutional Matrix Completion
Thomas N. Kipf Rianne van den Berg and Max Welling. 2017 · 2017
HOP-rec: high-order proximity for implicit recommendation
Chuan-Ju Wang Jheng-Hong Yang, Chih-Ming Chen and Ming-Feng Tsai. 2018 · 2018
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Representation Learning on Graphs with Jumping Knowledge Networks
Yonglong Tian Tomohiro Sonobe Ken-ichi Kawarabayashi and StefanieJegelka Keyulu Xu, Chengtao Li. 2018 · 2018
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Graph Convolutional Neural Networks for Web-Scale Recommender Systems
Kaifeng Chen Pong Eksombatchai William L. Hamilton Rex Ying, Ruining He and Jure Leskovec. 2018 · 2018
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Zero-shot recognition via semantic embeddings and knowledge graphs
Yufei Ye Xiaolong Wang and Abhinav Gupta. 2018 · 2018
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Simplifying Graph Convolutional Networks
Tianyi Zhang Christopher Fifty Tao Yu Felix Wu, Amauri H. Souza Jr. and Kilian Q. Weinberger. 2019 · 2019
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A Neural Influence Diffusion Model for Social Recommendation
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Inductive Representation Learning on Large Graphs
Zhitao Ying William L. Hamilton and Jure Leskovec. 2017 · 2017
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Neural Collaborative Filtering
Hanwang Zhang Liqiang Nie Xia Hu Xiangnan He, Lizi Liao and Tat-Seng Chua. 2017 · 2017
Cited alongside, same era.
BiRank:Towards Ranking on Bipartite Graphs
Min-Yen Kan Xiangnan He, Ming Gao and Dingxian Wang. 2017 · 2017
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Causal Embeddings for Recommendation
Stephen Bonner and Flavian Vasile. 2018 · 2018
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Yanjie Fu Richang Hong Xiting Wang Le Wu, Peijie Sun and Meng Wang. 2019 · 2019
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Neural Graph Collaborative Filtering
Meng Wang Fuli Feng Xiang Wang, Xiangnan He and Tat-Seng Chua. 2019a · 2019
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KGAT: Knowledge Graph Attention Network for Recommendation
Yixin Cao Meng Liu Xiang Wang, Xiangnan He and Tat-Seng Chua. 2019b · 2019
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Deep Item-based Collaborative Filtering for Top-N Recommendation
Feng Xue, Xiangnan He, Xiang Wang, Jiandong Xu, Kai Liu, and Richang Hong. 2019 · 2019
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Unifying Knowledge Graph Learning and Recommendation: Towards a Better Understanding of User Preferences
Xiangnan He Zikun Hu Yixin Cao, Xiang Wang and Tat-Seng Chua. 2019 · 2019
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