An Auxiliary Learning Task-Enhanced Graph Convolutional Network Model for Highly-accurate Node Classification on Weakly Supervised Graphs

Keyphrases

• Highly Accurate 100%
• Node Classification 100%
• Graph Convolutional Network 100%
• Auxiliary Learning Task 100%
• Weak Supervision 100%
• Convolutional Network Model 100%
• Learning Task 60%
• Convolutional Networks 40%
• Alpha Graphs 40%
• Performance Improvement 20%
• Model Selection 20%
• Challenging Issues 20%
• Networked Learning 20%
• Supervised Learning 20%
• Semi-supervised Learning 20%
• Graph Learning 20%
• Labeled Data 20%
• State-of-the-art Techniques 20%
• Model Learning 20%
• Labeled Graph 20%
• Unsupervised Learning 20%

Computer Science

• Node Classification 100%
• Graph Convolutional Network 100%
• Experimental Result 14%
• Learning Network 14%
• Supervised Learning 14%
• Semisupervised Learning 14%
• Performance Improvement 14%
• Labelled Graph 14%
• Unsupervised Learning 14%
• Model Selection 14%