A Lexicon Enhanced Chinese Long Named Entity Recognition Using Word-Aware Attention-Reference-Cited by-同舟云学术

A Lexicon Enhanced Chinese Long Named Entity Recognition Using Word-Aware Attention

Published:2023-12-27 Issue: Volume: Page:234-242
ISSN:
Container-title:Proceedings of the 2023 6th International Conference on Machine Learning and Natural Language Processing
language:
Short-container-title:

Author:

Wang Chen¹^ORCID,Xiong Xiong¹^ORCID,Wang Linjie¹^ORCID,Zheng Yifeng¹^ORCID,Liu Yunfei¹^ORCID,Li Shengyang¹^ORCID

Affiliation:

1. Key Laboratory of Space Utilization, Technology and Engineering Center for Space Utilization, Chinese Academy of Sciences, China and University of Chinese Academy of Sciences, China

Funder

Manned Space Engineering Project: Research on Technology and Method of Engineering Big Data Knowledge Mining

National Defense Science and Technology Key Laboratory Fund Project of the Chinese Academy of Sciences: Space Science and Application of Big Data Knowledge Graph Construction and Intelligent Application Research

National Basic Science Data Center China Manned Space Science and Applications DataBase

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3639479.3639527

Reference30 articles.

1. Zihang Dai, Zhilin Yang, Yiming Yang, Jaime G. Carbonell, Quoc V. Le, and Ruslan Salakhutdinov. 2019. Transformer-XL: Attentive Language Models beyond a Fixed-Length Context. ArXiv abs/1901.02860 (2019).

2. Chuanhai Dong, Jiajun Zhang, Chengqing Zong, Masanori Hattori, and Hui Di. 2016. Character-Based LSTM-CRF with Radical-Level Features for Chinese Named Entity Recognition. In Natural Language Understanding and Intelligent Applications, Chin-Yew Lin, Nianwen Xue, Dongyan Zhao, Xuanjing Huang, and Yansong Feng (Eds.). Springer International Publishing, Cham, 239–250.

3. A Transformer-Based Longer Entity Attention Model for Chinese Named Entity Recognition in Aerospace

4. Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence

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