Meta-based self-training and re-weighting for aspect-based sentiment analysis
Aspect-based sentiment analysis (ABSA) means to identify fine-grained aspects, opinions, and sentiment polarities. Recent ABSA research focuses on utilizing multi-task learning (MTL) to achieve less computational costs and better performance. However, there are certain limits in MTL-based ABSA. For...
Saved in:
Main Authors: | He, Kai, Mao, Rui, Gong, Tieliang, Li, Chen, Cambria, Erik |
---|---|
Other Authors: | School of Computer Science and Engineering |
Format: | Article |
Language: | English |
Published: |
2022
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/163145 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
Gender-based multi-aspect sentiment detection using multilabel learning
by: Kumar, J. Ashok, et al.
Published: (2022) -
Aspect-based Twitter sentiment classification
by: Lek, H.H., et al.
Published: (2014) -
Learning multi-grained aspect target sequence for Chinese sentiment analysis
by: Peng, Haiyun, et al.
Published: (2020) -
A convolutional stacked bidirectional LSTM with a multiplicative attention mechanism for aspect category and sentiment detection
by: Kumar, Ashok J., et al.
Published: (2022) -
Sentic LSTM : a hybrid network for targeted aspect-based sentiment analysis
by: Ma, Yukun, et al.
Published: (2020)