Chinese Event Extraction Based on Attention and Semantic Features: A Bidirectional Circular Neural Network
Chinese event extraction uses word embedding to capture similarity, but suffers when handling previously unseen or rare words. From the test, we know that characters may provide some information that we cannot obtain in words, so we propose a novel architecture for combining word representations: ch...
Main Authors: | Yue Wu, Junyi Zhang |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2018-09-01
|
Series: | Future Internet |
Subjects: | |
Online Access: | http://www.mdpi.com/1999-5903/10/10/95 |
Similar Items
-
Chinese Event Detection Based on Multi-Feature Fusion and BiLSTM
by: Guixian Xu, et al.
Published: (2019-01-01) -
Emotion-Semantic-Enhanced Bidirectional LSTM with Multi-Head Attention Mechanism for Microblog Sentiment Analysis
by: Shaoxiu Wang, et al.
Published: (2020-05-01) -
Make It Directly: Event Extraction Based on Tree-LSTM and Bi-GRU
by: Wentao Yu, et al.
Published: (2020-01-01) -
An Attention Enhanced Bidirectional LSTM for Early Forest Fire Smoke Recognition
by: Yichao Cao, et al.
Published: (2019-01-01) -
A Novel PPA Method for Fluid Pipeline Leak Detection Based on OPELM and Bidirectional LSTM
by: Lei Yang, et al.
Published: (2020-01-01)