Chinese relation extraction based on characters and words fusion

Wenxiu Bu; Wenzhong Yang; Danny Chen; Tiantian Ding

doi:10.1117/12.2646788

7 September 2022 Chinese relation extraction based on characters and words fusion

Wenxiu Bu, Wenzhong Yang, Danny Chen, Tiantian Ding

Proceedings Volume 12329, Third International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2022); 123291A (2022) https://doi.org/10.1117/12.2646788
Event: Third International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2022), 2022, Changsha, China

Abstract

Chinese relation extraction is designed to extract the relation between a given entity pair from unstructured text. Neither existing character input-based nor word-input methods can take full advantage of the semantic information in the data. Although studies have explored this, there are still problems with the lack of semantic information and the low speed of reasoning. To address the issues, we propose FCW-BERT: Fuse Characters and Words-BERT for Chinese RE, which add word information in a flat structure as input, and enhance the interaction between characters and words with a relative position encoding. Furthermore, we utilize TextCNN for further local feature extraction, experiments on two real-world datasets in distinct domains show consistent and significant superiority and robustness of our model, as compared with other baselines.

Citation Download Citation

Wenxiu Bu, Wenzhong Yang, Danny Chen, and Tiantian Ding "Chinese relation extraction based on characters and words fusion", Proc. SPIE 12329, Third International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2022), 123291A (7 September 2022); https://doi.org/10.1117/12.2646788

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available