Adaptive feature interaction enhancement network for text classification
Abstract Text classification aims to establish text distinctions, which face difficulty in capturing global text semantics and local details. To address this issue, we propose an Adaptive Feature Interactive Enhancement Network (AFIENet). Specifically, AFIENet uses two branches to model the text glo...
Saved in:
| Main Authors: | Rui Su, Shangbing Gao, Kefan Zhao, Junqiang Zhang |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-04-01
|
| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-95492-y |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Text Classification by Genre Based on Rhythm Features
by: Ksenia Vladimirovna Lagutina, et al.
Published: (2021-10-01) -
Study of the Application of Text Augmentation with Paraphrasing to Overcome Imbalanced Data in Indonesian Text Classification
by: Mutiara Indryan Sari, et al.
Published: (2025-04-01) -
Research on Aerospace Text Classification Based on BERT-LSTM Model
by: AN Rui, et al.
Published: (2024-08-01) -
Comprehensive Study on Zero-Shot Text Classification Using Category Mapping
by: Kai Zhang, et al.
Published: (2025-01-01) -
A text classification model for dynamic fusion of global and local features
by: ZHENG Wenjun, et al.
Published: (2024-08-01)