Attention-Based Graph Neural Network with Global Context Awareness for Document Understanding

Author:

Hua Yuan,Huang Zheng,Guo Jie,Qiu Weidong

Publisher

Springer International Publishing

Reference21 articles.

1. Akbik, A., Bergmann, T., Vollgraf, R.: Pooled contextualized embeddings for named entity recognition. In: Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers), pp. 724–728 (2019)

2. Chiticariu, L., Li, Y., Reiss, F.: Rule-based information extraction is dead! long live rule-based information extraction systems! In: Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing, pp. 827–832 (2013)

3. Lecture Notes in Computer Science;AR Dengel,2002

4. Devlin, J., Chang, M.W., Lee, K., Toutanova, K.: Bert: pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805 (2018)

5. Gui, T., et al.: A lexicon-based graph neural network for Chinese NER. In: Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), pp. 1039–1049 (2019)

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