Knowledge Graph Convolutional Networks for Recommender Systems

Author:

Wang Hongwei1,Zhao Miao2,Xie Xing3,Li Wenjie2,Guo Minyi4

Affiliation:

1. Shanghai Jiao Tong University Shanghai, China

2. The Hong Kong Polytechnic University, Hong Kong, China

3. Microsoft Research Asia Beijing, China

4. Shanghai Jiao Tong University Shanghai, China guo-my@cs.sjtu.edu.cn

Publisher

ACM Press

Reference26 articles.

1. Antoine Bordes, Nicolas Usunier, Alberto Garcia-Duran, Jason Weston, and Oksana Yakhnenko. 2013. Translating embeddings for modeling multi-relational data. In Advances in Neural Information Processing Systems. 2787-2795.

2. Joan Bruna, Wojciech Zaremba, Arthur Szlam, and Yann Lecun. 2014. Spectral networks and locally connected networks on graphs. In the 2nd International Conference on Learning Representations.

3. Heng-Tze Cheng, Levent Koc, Jeremiah Harmsen, Tal Shaked, Tushar Chandra, Hrishi Aradhye, Glen Anderson, Greg Corrado, Wei Chai, Mustafa Ispir, 2016. Wide & deep learning for recommender systems. In Proceedings of the 1st Workshop on Deep Learning for Recommender Systems. ACM, 7-10.

4. Michaël Defferrard, Xavier Bresson, and Pierre Vandergheynst. 2016. Convolutional neural networks on graphs with fast localized spectral filtering. In Advances in Neural Information Processing Systems. 3844-3852.

5. Qiming Diao, Minghui Qiu, Chao-Yuan Wu, Alexander J Smola, Jing Jiang, and Chong Wang. 2014. Jointly modeling aspects, ratings and sentiments for movie recommendation (JMARS). In Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ACM, 193-202.

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