Applications of Named Entity Recognition Using Graph Convolution Network

Author:

Madan MonicaORCID,Rani Ashima,Bhateja Neha

Publisher

Springer Science and Business Media LLC

Subject

Computer Science Applications,Computer Networks and Communications,Computer Graphics and Computer-Aided Design,Computational Theory and Mathematics,Artificial Intelligence,General Computer Science

Reference22 articles.

1. Kipf TN, Welling M. Semi-supervised classification with graph convolutional networks. ICLR (2017).

2. Guo K, Hu Y, Qian Z, Liu H, Zhang K, Sun Y, et al. Optimized graph convolution recurrent neural network for traffic prediction. IEEE Trans Intell Transport Syst. 2021;22(2):1138–49.

3. Yao L, Mao C, Luo Y. Graph convolutional networks for text classification. In: Proceedings of the thirty-third AAAI conference on artificial intelligence and thirty-first innovative applications of artificial intelligence conference and ninth AAAI symposium on educational advances in artificial intelligence (AAAI’19/IAAI’19/EAAI’19). Palo Alto: AAAI Press; 2019. p. 7370–7.

4. Zhang J. Combining GCN and transformer for Chinese grammatical error detection. arXiv:2105.09085 [Preprint]. Available from: https://arXiv.org/abs/2105.09085 (2021).

5. Vashishth S, Dasgupta SS, Ray SN, Talukdar P. Dating documents using graph convolution networks. In: Proceedings of the 56th annual meeting of the association for computational linguistics. Melbourne: Association for Computational Linguistics; 2019. p. 1605–15.

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