Electric Power Audit Text Classification With Multi-Grained Pre-Trained Language Model
Electric power audit text classification is one of the important research problem in electric power systems. Recently, kinds of automatic classification methods for these texts based on machine learning or deep learning models have been applied. At present, the development of computing technology ma...
Main Authors: | Qinglin Meng, Yan Song, Jian Mu, Yuanxu Lv, Jiachen Yang, Liang Xu, Jin Zhao, Junwei Ma, Wei Yao, Rui Wang, Maoxiang Xiao, Qingyu Meng |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2023-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/10026821/ |
Similar Items
-
Pre-Trained Transformer-Based Models for Text Classification Using Low-Resourced Ewe Language
by: Victor Kwaku Agbesi, et al.
Published: (2023-12-01) -
Multilingual Text Summarization for German Texts Using Transformer Models
by: Tomas Humberto Montiel Alcantara, et al.
Published: (2023-05-01) -
Transformer-Based Composite Language Models for Text Evaluation and Classification
by: Mihailo Škorić, et al.
Published: (2023-11-01) -
Fiscal data in text: Information extraction from audit reports using Natural Language Processing
by: Alejandro Beltran
Published: (2023-01-01) -
Fine-Grained Sentiment-Controlled Text Generation Approach Based on Pre-Trained Language Model
by: Linan Zhu, et al.
Published: (2022-12-01)