Wacml: based on graph neural network for imbalanced node classification algorithm

Junfeng Wang; Jia‐Yue Yang; Lidun

doi:10.1007/s00530-024-01454-1

ScienceGate Book Chapters

JOURNAL ARTICLE

Wacml: based on graph neural network for imbalanced node classification algorithm

Junfeng Wang Jia‐Yue Yang Lidun

Year: 2024 Journal: Multimedia Systems Vol: 30 (5) Publisher: Springer Science+Business Media

DOI: 10.1007/s00530-024-01454-1

Get Full-Text PDF Get Analytical Report

Keywords:

Computer science Artificial neural network Node (physics) Cryptography Graph Algorithm Artificial intelligence Data mining Theoretical computer science Machine learning

Metrics

Cited By

1.92

FWCI (Field Weighted Citation Impact)

Refs

0.83

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Imbalanced Data Classification Techniques

Physical Sciences → Computer Science → Artificial Intelligence

Internet Traffic Analysis and Secure E-voting

Physical Sciences → Computer Science → Artificial Intelligence

Spam and Phishing Detection

Physical Sciences → Computer Science → Information Systems

Wacml: based on graph neural network for imbalanced node classification algorithm

Metrics

Citation History

Topics

Related Documents

A graph neural network-based node classification model on class-imbalanced graph data

Graph Neural Network with curriculum learning for imbalanced node classification

Implementation of Node Classification Algorithm Based on Graph Neural Network

Heterophily-Based Graph Neural Network for Imbalanced Classification

Graph Neural Network with Adaptive Node-Edge Augmentation Strategies for Imbalanced Node Classification