Entity and relation collaborative extraction approach based on multi-head attention and gated mechanism-Reference-Cited by-同舟云学术

Entity and relation collaborative extraction approach based on multi-head attention and gated mechanism

Published:2022-02-04 Issue:1 Volume:34 Page:670-686
ISSN:0954-0091
Container-title:Connection Science
language:en
Short-container-title:Connection Science

Author:

Zhao Wei¹²,Zhao Shan¹,Chen Shuhui¹,Weng Tien-Hsiung³,Kang WenJie²⁴

Affiliation:

1. College of Computer, National University of Defense Technology, Changsha, People's Republic of China

2. Hunan Provincial Key Laboratory of Network Investigational Technology, Hunan Police Academy, Changsha, Hunan, People's Republic of China

3. Department of Computer Science and Information Engineering Providence University Taiwan, Computer Science and Information Engineering Providence University Taiwan, Taichung City Taiwan

4. Science and Technology on Information Systems Engineering Laboratory, National University of Defense Technology, Changsha, People's Republic of China

Funder

Scientific Research Fund of Hunan Provincial Education Department

Changsha Municipal Natural Science Foundation

Hunan Province Scientific Research Project

The Hunan Social Science Fund

High-tech Industry Science and Technology Innovation Leading Plan

Open Research Fund of Hunan Provincial Key Laboratory of Network Investigational Technology

Publisher

Informa UK Limited

Subject

Artificial Intelligence,Human-Computer Interaction,Software

Link

https://www.tandfonline.com/doi/pdf/10.1080/09540091.2022.2026295

Reference61 articles.

1. Adel, H. & Schütze, H. (2017). Global normalization of convolutional neural networks for joint entity and relation classification. arXiv preprint arXiv:1707.07719.

2. On the Estimation and Control of Nonlinear Systems With Parametric Uncertainties and Noisy Outputs

3. Bahdanau, D., Cho, K. & Bengio, Y. (2014). Neural machine translation by jointly learning to align and translate. arXiv preprint arXiv:1409.0473.

4. Adversarial training for multi-context joint entity and relation extraction

5. Joint entity recognition and relation extraction as a multi-head selection problem

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