Comparative Study of Deep Learning-Based Sentiment Classification
The purpose of sentiment classification is to determine whether a particular document has a positive or negative nuance. Sentiment classification is extensively used in many business domains to improve products or services by understanding the opinions of customers regarding these products. Deep lea...
Saved in:
| Main Authors: | Seungwan Seo, Czangyeob Kim, Haedong Kim, Kyounghyun Mo, Pilsung Kang |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2020-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/8948030/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Dynamic Text Augmentation for Robust Sentiment Analysis: Enhancing Model Performance With EDA and Multi-Channel CNN
by: Komang Wahyu Trisna, et al.
Published: (2025-01-01) -
Fusion Text Representations to Enhance Contextual Meaning in Sentiment Classification
by: Komang Wahyu Trisna, et al.
Published: (2024-11-01) -
Application of embeddings for multi-class classification with optional extendability
by: Ф. Смілянець
Published: (2024-10-01) -
Survey of text classification methods based on deep learning
by: Sijia DU, et al.
Published: (2020-08-01) -
Short Text Classification Based on Enhanced Word Embedding and Hybrid Neural Networks
by: Cunhe Li, et al.
Published: (2025-05-01)