Label-Aware Hierarchical Ranking Model for Multi-Label Text Classification
Multi-label text classification involves assigning multiple relevant categories to a single text, enabling applications in academic indexing, medical diagnostics, and e-commerce. However, existing models often fail to capture complex text-label relationships and lack robust mechanisms for ranking la...
Saved in:
| Main Authors: | Lama Ayash, Abdulmohsen Algarni, Omar Alqahtani |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/11129041/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Hierarchical contrastive learning for multi-label text classification
by: Wei Zhang, et al.
Published: (2025-04-01) -
Hierarchical multi-instance multi-label learning for Chinese patent text classification
by: Yunduo Liu, et al.
Published: (2024-12-01) -
CQL-GNN: Coupled question-label graph neural networks for multi-label educational question classification
by: Liwei Gao, et al.
Published: (2025-08-01) -
Advancements in feature selection and extraction methods for text mining: a review
by: Lama Ayash, et al.
Published: (2025-08-01) -
Multi-label Text Classification by Fusing Pseudo-label Generation and Data Augmentation
by: WANG Shuitao, et al.
Published: (2024-12-01)