All is attention for multi-label text classification

Zhiyi Liu; Yunjie Huang; Xincheng Xia; Yihao Zhang

doi:10.1007/s10115-024-02253-w

ScienceGate Book Chapters

JOURNAL ARTICLE

All is attention for multi-label text classification

Zhiyi Liu Yunjie Huang Xincheng Xia Yihao Zhang

Year: 2024 Journal: Knowledge and Information Systems Vol: 67 (2)Pages: 1249-1270 Publisher: Springer Science+Business Media

DOI: 10.1007/s10115-024-02253-w

Get Full-Text PDF Get Analytical Report

Keywords:

Computer science Exploit Embedding Graph Multi-label classification Artificial intelligence Machine learning Feature (linguistics) Class (philosophy) Natural language processing Theoretical computer science

Metrics

Cited By

4.47

FWCI (Field Weighted Citation Impact)

Refs

0.92

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Text and Document Classification Technologies

Physical Sciences → Computer Science → Artificial Intelligence

Topic Modeling

Physical Sciences → Computer Science → Artificial Intelligence

Sentiment Analysis and Opinion Mining

Physical Sciences → Computer Science → Artificial Intelligence

All is attention for multi-label text classification

Metrics

Citation History

Topics

Related Documents

Multi-Label Text Classification model integrating Label Attention and Historical Attention

Label-text bi-attention capsule networks model for multi-label text classification

Multi Label Clinical Text Classification Using Attention Mechanism

Multi-Label Text Classification Based on BERT and Label Attention Mechanism

BeNet: BERT Doc-Label Attention Network for Multi-Label Text Classification