Introduction to Knowledge Graph-Based Recommender Systems | by Amine Dadoun | Apr, 2023


[1] Zhu Sun, Jie Yang, Jie Zhang, Alessandro Bozzon, Long-Kai Huang, and Chi Xu. Recurrent knowledge graph embedding for effective recommendation. In Proceedings of the 12th ACM Conference on Recommender Systems, RecSys ’18, page 297–305, New York, NY, USA, 2018. Association for Computing Machinery.

[2] Antoine Bordes, Nicolas Usunier, Alberto Garcia-Duran, Jason Weston, and Oksana Yakhnenko. Translating embeddings for modeling multi-relational data. In C. J. C. Burges, L. Bottou, M. Welling, Z. Ghahramani, and K. Q. Weinberger, editors, Advances in Neural Information Processing Systems, volume 26, Lake Tahoe, Nevada, United States, 2013. Curran Associates, Inc.

[3] Fuzheng Zhang, Nicholas Jing Yuan, Defu Lian, Xing Xie, and Wei-Ying Ma. Collaborative Knowledge Base Embedding for Recommender Systems. In 22Nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 353–362, New York, NY, USA, 2016. AC

[4] Yongfeng Zhang, Qingyao Ai, Xu Chen, and Pengfei Wang. Learning over knowledgebase embeddings for recommendation. CoRR, abs/1803.06540, 2018.

[5] Xiao Yu, Xiang Ren, Yizhou Sun, Quanquan Gu, Bradley Sturt, Urvashi Khandelwal, Brandon Norick, and Jiawei Han. Personalized entity recommendation: A heterogeneous information network approach. In Proceedings of the 7th ACM International Conference on Web Search and Data Mining, WSDM ’14, page 283–292, New York, NY, USA, 2014. Association for Computing Machinery.

[6] Huan Zhao, Quanming Yao, Jianda Li, Yangqiu Song, and Dik Lun Lee. Meta-graph based recommendation fusion over heterogeneous information networks. In Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD ’17, page 635–644, New York, NY, USA, 2017. Association for Computing Machinery.

[7] Hongwei Wang, Fuzheng Zhang, Jialin Wang, Miao Zhao, Wenjie Li, Xing Xie, and Minyi Guo. 2018. RippleNet: Propagating User Preferences on the Knowledge Graph for Recommender Systems. In Proceedings of the 27th ACM International Conference on Information and Knowledge Management (CIKM ‘18). Association for Computing Machinery, New York, NY, USA, 417–426.



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