Interactive Rule Attention Network for Aspect-Level Sentiment Analysis
Aspect-level sentiment analysis is a fundamental task in NLP, and it aims to predict the sentiment polarity of each specific aspect term in a given sentence. Recent researches show that the fine-grained sentiment analysis for aspect-level has become a research hotspot. However, previous work did not...
Main Authors: | Qiang Lu, Zhenfang Zhu, Dianyuan Zhang, Wenqing Wu, Qiangqiang Guo |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2020-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/9037260/ |
Similar Items
-
Multiple Interactive Attention Networks for Aspect-Based Sentiment Classification
by: Dianyuan Zhang, et al.
Published: (2020-03-01) -
Bi-GRU Sentiment Classification for Chinese Based on Grammar Rules and BERT
by: Qiang Lu, et al.
Published: (2020-05-01) -
Interactive Multi-Head Attention Networks for Aspect-Level Sentiment Classification
by: Qiuyue Zhang, et al.
Published: (2019-01-01) -
A Multi-Attention Network for Aspect-Level Sentiment Analysis
by: Qiuyue Zhang, et al.
Published: (2019-07-01) -
Aspect-Context Interactive Attention Representation for Aspect-Level Sentiment Classification
by: Zhuojia Wu, et al.
Published: (2020-01-01)