Relation extraction based on CNN and Bi-LSTM
Relation extraction aims to identify the entities in the Web text and extract the implicit relationships between entities in the text.Studies have shown that deep neural networks are feasible for relation extraction tasks and are superior to traditional methods.Most of the current relation extractio...
Saved in:
Main Authors: | Xiaobin ZHANG, Fucai CHEN, Ruiyang HUANG |
---|---|
Format: | Article |
Language: | English |
Published: |
POSTS&TELECOM PRESS Co., LTD
2018-09-01
|
Series: | 网络与信息安全学报 |
Subjects: | |
Online Access: | http://www.cjnis.com.cn/thesisDetails#10.11959/j.issn.2096-109x.2018074 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A file archival integrity check method based on the BiLSTM + CNN model and deep learning
by: Jinxun Li, et al.
Published: (2025-03-01) -
A hybrid CNN-Bi-LSTM model with feature fusion for accurate epilepsy seizure detection
by: Xiaoshuai Cao, et al.
Published: (2025-01-01) -
Energy consumption prediction using modified deep CNN-Bi LSTM with attention mechanism
by: Adel Binbusayyis, et al.
Published: (2025-01-01) -
Residual Life Prediction of SA-CNN-BILSTM Aero-Engine Based on a Multichannel Hybrid Network
by: Yonghao He, et al.
Published: (2025-01-01) -
Integrated CNN‐LSTM for Photovoltaic Power Prediction based on Spatio‐Temporal Feature Fusion
by: Junwei Ma, et al.
Published: (2025-01-01)