Research on relationship extraction model for Xizang script named entities integrating category keywords and graph neural network

Jiangyong Tudeng; Lanqing Ou; Pengcuo Dawa

doi:10.1117/12.3026099

6 May 2024 Research on relationship extraction model for Xizang script named entities integrating category keywords and graph neural network

Jiangyong Tudeng, Lanqing Ou, Pengcuo Dawa

Author Affiliations +

Proceedings Volume 13161, Fourth International Conference on Telecommunications, Optics, and Computer Science (TOCS 2023); 131610R (2024) https://doi.org/10.1117/12.3026099
Event: Fourth International Conference on Telecommunications, Optics and Computer Science (TOCS 2023), 2023, Xi’an, China

Abstract

The Xizang script named entity relationship extraction is the foundation and premise of information processing such as machine translation, knowledge graph and network public opinion analysis, the traditional Xizang script named entity relationship extraction based on deep learning may often ignore Category Keywords. This paper applies the Xizang script entity relationship extraction method of graph convolutional neural network (GCN). On the basis of the original word vector, category keyword characteristics are obtained through a keyword acquisition algorithm, and a segmented maximum pooling strategy is used to reduce the loss of information in traditional maximum pooling strategies, the maximum pooling strategy for the pooling process is to select the characteristic with the highest score from a series of characteristic values obtained from each filter in the convolutional layer as the reserved value of the pooling layer. Experiments have shown that the method in this paper significantly enhances the results of extracting Xizang script entity relationships.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Jiangyong Tudeng, Lanqing Ou, and Pengcuo Dawa "Research on relationship extraction model for Xizang script named entities integrating category keywords and graph neural network", Proc. SPIE 13161, Fourth International Conference on Telecommunications, Optics, and Computer Science (TOCS 2023), 131610R (6 May 2024); https://doi.org/10.1117/12.3026099

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