Learning multi-grained aspect target sequence for Chinese sentiment analysis
Aspect-based sentiment analysis aims at identifying sentiment polarity towards aspect targets in a sentence. Previously, the task was modeled as a sentence-level sentiment classification problem that treated aspect targets as a hint. Such approaches oversimplify the problem by averaging word embeddi...
Saved in:
Main Authors: | Peng, Haiyun, Ma, Yukun, Li, Yang, Cambria, Erik |
---|---|
Other Authors: | School of Computer Science and Engineering |
Format: | Article |
Language: | English |
Published: |
2020
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/139596 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
NEURAL FINE-GRAINED SENTIMENT ANALYSIS WITH UNSUPERVISED AND TRANSFER LEARNING APPROACHES
by: HE RUIDAN
Published: (2020) -
Sentic LSTM : a hybrid network for targeted aspect-based sentiment analysis
by: Ma, Yukun, et al.
Published: (2020) -
Phonetic-enriched text representation for Chinese sentiment analysis with reinforcement learning
by: Peng, Haiyun, et al.
Published: (2022) -
Towards a Chinese common and common sense knowledge base for sentiment analysis
by: Cambria, E., et al.
Published: (2014) -
Aspect-based Twitter sentiment classification
by: Lek, H.H., et al.
Published: (2014)