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Recent advances in research have demonstrated the effectiveness of knowledge graphs (KG) in providing valuable external knowledge to improve recommendation systems (RS).
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Item silk road: Recommending items from information domains to social users. In Proceedings of the 40th International ACM SIGIR conference on Research and Development in Information Retrieval . 185–194
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Attentional Factorization Machines: Learning the Weight of Feature Interactions via Attention Networks. In Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, IJCAI 2017, Melbourne, Australia, August 19-25, 2017 . 3119–3125
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Explicit semantic ranking for academic search via knowledge graph embedding. In Proceedings of the 26th international conference on world wide web . 1271–1279
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A Fairness-aware Hybrid Recommender System
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Cross-language citation recommendation via hierarchical representation learning on heterogeneous graph. In The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval . 635–644
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User Fairness in Recommender Systems. In Companion of the The Web Conference 2018 on The Web Conference 2018, WWW 2018, Lyon , France, April 23-27, 2018 . 101–102
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Explainable Interaction-driven User Modeling over Knowledge Graph for Sequential Recommendation. In Proceedings of the 27th ACM International Conference on Multimedia, MM 2019, Nice, France, October 21-25, 2019 . 548–556
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Long-tail Hashtag Recommendation for Micro-videos with Graph Convolutional Network. In Proceedings of the 28th ACM International Conference on Information and Knowledge Management . 509–518
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Jointly Learning Explainable Rules for Recommendation with Knowledge Graph. In The World Wide Web Conference, WWW 2019, San Francisco, CA, USA, May 13-17, 2019 . 1210–1221
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Explainability Methods for Graph Convolutional Neural Networks. In IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2019, Long Beach, CA, USA, June 16-20, 2019 . 10772–10781
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Ever get caught in an unexpected hourlong YouTube binge? Thank YouTube AI for that
Joan E. Solsman. 2018 · 2018
Cited alongside, same era.
Recurrent knowledge graph embedding for effective recommendation. In Proceedings of the 12th ACM Conference on Recommender Systems, RecSys 2018, Vancouver, BC, Canada, October 2-7, 2018 . 297–305
Zhu Sun, Jie Yang, Jie Zhang, Alessandro Bozzon, Long-Kai Huang, and Chi Xu. 2018a · 2018
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Latent Relational Metric Learning via Memory-based Attention for Collaborative Ranking. In Proceedings of the 2018 World Wide Web Conference on World Wide Web, WWW 2018, Lyon, France, April 23-27, 2018 . 729–739
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Graph Attention Networks. In 6th International Conference on Learning Representations, ICLR 2018, Vancouver, BC, Canada, April 30 - May 3, 2018, Conference Track Proceedings
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Cited alongside, same era.
DKN: Deep knowledge-aware network for news recommendation. In Proceedings of the 2018 world wide web conference . 1835–1844
Hongwei Wang, Fuzheng Zhang, Xing Xie, and Minyi Guo. 2018 · 2018
Cited alongside, same era.
Graph convolutional neural networks for web-scale recommender systems. In Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining . 974–983
Rex Ying, Ruining He, Kaifeng Chen, Pong Eksombatchai, William L Hamilton, and Jure Leskovec. 2018 · 2018
Cited alongside, same era.
Fairness in Recommendation Ranking through Pairwise Comparisons. In Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, KDD 2019, Anchorage, AK, USA, August 4-8, 2019 . 2212–2220
Alex Beutel, Jilin Chen, Tulsee Doshi, Hai Qian, Li Wei, Yi Wu, Lukasz Heldt, Zhe Zhao, Lichan Hong, Ed H. Chi, and Cristos Goodrow. 2019 · 2019
Cited alongside, same era.
Metapath-guided Heterogeneous Graph Neural Network for Intent Recommendation. In Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, KDD 2019, Anchorage, AK, USA, August 4-8, 2019 . 2478–2486
Shaohua Fan, Junxiong Zhu, Xiaotian Han, Chuan Shi, Linmei Hu, Biyu Ma, and Yongliang Li. 2019c · 2019
Cited alongside, same era.
Phillip E. Pope, Soheil Kolouri, Mohammad Rostami, Charles E. Martin, and Heiko Hoffmann. 2019 · 2019
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Session-Based Social Recommendation via Dynamic Graph Attention Networks. In Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining, WSDM 2019, Melbourne, VIC, Australia, February 11-15, 2019 . 555–563
Weiping Song, Zhiping Xiao, Yifan Wang, Laurent Charlin, Ming Zhang, and Jian Tang. 2019 · 2019
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Knowledge Graph Convolutional Networks for Recommender Systems. In The World Wide Web Conference, WWW 2019, San Francisco, CA, USA, May 13-17, 2019 . 3307–3313
Hongwei Wang, Miao Zhao, Xing Xie, Wenjie Li, and Minyi Guo. 2019e · 2019
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KGAT: Knowledge Graph Attention Network for Recommendation. In Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, KDD 2019, Anchorage, AK, USA, August 4-8, 2019 . 950–958
Xiang Wang, Xiangnan He, Yixin Cao, Meng Liu, and Tat-Seng Chua. 2019a · 2019
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Explainable Reasoning over Knowledge Graphs for Recommendation. In The Thirty-Third AAAI Conference on Artificial Intelligence, AAAI 2019, The Thirty-First Innovative Applications of Artificial Intelligence Conference, IAAI 2019, The Ninth AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019, Honolulu, Hawaii, USA, January 27 - February 1, 2019 . 5329–5336
Xiang Wang, Dingxian Wang, Canran Xu, Xiangnan He, Yixin Cao, and Tat-Seng Chua. 2019c · 2019
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Relation-Aware Graph Convolutional Networks for Agent-Initiated Social E-Commerce Recommendation. In Proceedings of the 28th ACM International Conference on Information and Knowledge Management . 529–538
Fengli Xu, Jianxun Lian, Zhenyu Han, Yong Li, Yujian Xu, and Xing Xie. 2019 · 2019
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GNNExplainer: Generating Explanations for Graph Neural Networks. In Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, NeurIPS 2019, 8-14 December 2019, Vancouver, BC, Canada . 9240–9251
Zhitao Ying, Dylan Bourgeois, Jiaxuan You, Marinka Zitnik, and Jure Leskovec. 2019 · 2019
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STAR-GCN: Stacked and Reconstructed Graph Convolutional Networks for Recommender Systems. In Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, IJCAI 2019, Macao, China, August 10-16, 2019 . 4264–4270
Jiani Zhang, Xingjian Shi, Shenglin Zhao, and Irwin King. 2019 · 2019
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IntentGC: a Scalable Graph Convolution Framework Fusing Heterogeneous Information for Recommendation. In Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining . 2347–2357
Jun Zhao, Zhou Zhou, Ziyu Guan, Wei Zhao, Wei Ning, Guang Qiu, and Xiaofei He. 2019 · 2019
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Dual graph attention networks for deep latent representation of multifaceted social effects in recommender systems. In The World Wide Web Conference . 2091–2102
Qitian Wu, Hengrui Zhang, Xiaofeng Gao, Peng He, Paul Weng, Han Gao, and Guihai Chen. 2019c · 2091
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