Optimized Reinforcement Learning Model via Contrastive Learning for Intention Classification of Chinese Questions on Respiratory Diseases
The intent classification of Chinese questions on respiratory diseases (IC-CQRD) can not only promote the development of smart medical care, but also strengthen epidemic surveillance. To address the limited availability of datasets in this field, we have developed the IC-CQRD dataset. The core of IC...
Saved in:
| Main Authors: | Hao Wu, Degen Huang, Xiaohui Lin |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/11025125/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Reinforcement Learning-Based Intent Classification of Chinese Questions About Respiratory Diseases
by: Hao Wu, et al.
Published: (2025-04-01) -
Explicit intent enhanced contrastive learning with denoising networks for sequential recommendation
by: Jinfang Sheng, et al.
Published: (2025-05-01) -
CycleGuardian: a framework for automatic respiratory sound classification based on improved deep clustering and contrastive learning
by: Yun Chu, et al.
Published: (2025-03-01) -
3D LiDAR Multi-Object Tracking Using Multi Positive Contrastive Learning and Deep Reinforcement Learning
by: Minho Cho, et al.
Published: (2025-01-01) -
DEANE: Context-Aware Dual-Craft Graph Contrastive Learning for Enhanced Extractive Question Answering
by: Dongfen Ye, et al.
Published: (2025-04-01)