Taxonomy-Enhanced Graph Neural Networks

Author:

Xu Lingjun1,Zhang Shiyin1,Song Guojie1,Wang Junshan2,Wu Tianshu2,Liu Guojun2

Affiliation:

1. Peking University, Beijing, China

2. Alibaba Group, Beijing, China

Funder

National Natural Science Foundation of China

Publisher

ACM

Reference38 articles.

1. Ines Chami , Zhitao Ying , Christopher Ré , and Jure Leskovec . 2019. Hyperbolic graph convolutional neural networks. Advances in neural information processing systems , Vol. 32 ( 2019 ). Ines Chami, Zhitao Ying, Christopher Ré, and Jure Leskovec. 2019. Hyperbolic graph convolutional neural networks. Advances in neural information processing systems, Vol. 32 (2019).

2. node2vec

3. Bronwyn H Hall , Adam B Jaffe , and Manuel Trajtenberg . 2001. The NBER Patent Citation Data File: Lessons, Insights and Methodological Tools. Working Paper 8498 . National Bureau of Economic Research . https://doi.org/10.3386/w8498 10.3386/w8498 Bronwyn H Hall, Adam B Jaffe, and Manuel Trajtenberg. 2001. The NBER Patent Citation Data File: Lessons, Insights and Methodological Tools. Working Paper 8498. National Bureau of Economic Research. https://doi.org/10.3386/w8498

4. Will Hamilton , Zhitao Ying , and Jure Leskovec . 2017. Inductive representation learning on large graphs. Advances in neural information processing systems , Vol. 30 ( 2017 ). Will Hamilton, Zhitao Ying, and Jure Leskovec. 2017. Inductive representation learning on large graphs. Advances in neural information processing systems, Vol. 30 (2017).

5. Mikael Henaff , Joan Bruna , and Yann LeCun . 2015. Deep convolutional networks on graph-structured data. arXiv preprint arXiv:1506.05163 ( 2015 ). Mikael Henaff, Joan Bruna, and Yann LeCun. 2015. Deep convolutional networks on graph-structured data. arXiv preprint arXiv:1506.05163 (2015).

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