CRSAtt: By Capturing Relational Span and Using Attention for Relation Classification
Relation classification is an important fundamental task in information extraction, and convolutional neural networks have been commonly applied to relation classification with good results. In recent years, due to the proposed pre-training model BERT, the use of which as a feature extraction archit...
Main Authors: | Cong Shao, Min Li, Gang Li, Mingle Zhou, Delong Han |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2022-11-01
|
Series: | Applied Sciences |
Subjects: | |
Online Access: | https://www.mdpi.com/2076-3417/12/21/11068 |
Similar Items
-
FA-RCNet: A Fused Feature Attention Network for Relationship Classification
by: Jiakai Tian, et al.
Published: (2022-12-01) -
Entity Relation Extraction Method Integrating Pre-trained Model and Attention
by: LI Zhijie, HAN Ruirui, LI Changhua, ZHANG Jie, SHI Haoqi
Published: (2023-06-01) -
A Multiscale Self-Adaptive Attention Network for Remote Sensing Scene Classification
by: Lingling Li, et al.
Published: (2020-07-01) -
A Spectral Spatial Attention Fusion with Deformable Convolutional Residual Network for Hyperspectral Image Classification
by: Tianyu Zhang, et al.
Published: (2021-09-01) -
Dynamic Convolution Self-Attention Network for Land-Cover Classification in VHR Remote-Sensing Images
by: Xuan Wang, et al.
Published: (2022-10-01)