On Representation Learning for Road Networks

Computer Science

• Representation Learning 100%
• Component Analysis 66%
• Principal Components 66%
• Experimental Result 33%
• Neural Network Model 33%
• Topological Structure 33%
• Learning Framework 33%
• Intrinsic Property 33%
• Traffic Signal 33%
• Intelligent Transportation System 33%
• Network Structure 33%
• Data Preparation 33%
• Mean Absolute Error 33%
• Graph Convolutional Network 33%
• Node2Vec 33%
• Graph Attention Network 33%

Keyphrases

• Road Network 100%
• Representation Learning 100%
• Road Segment 37%
• Principal Coordinate Analysis (PCoA) 25%
• Travel Time Estimation 25%
• Network Structure 12%
• Neural Network Model 12%
• Traffic Signals 12%
• Feature-based 12%
• Intrinsic Properties 12%
• Model Design 12%
• F1 Score 12%
• Topological Structure 12%
• Network Framework 12%
• New Learning 12%
• Substructure Method 12%
• Classification Time 12%
• Learning Framework 12%
• Intelligent Transportation Systems 12%
• Mean Absolute Error 12%
• Network Embedding 12%
• Network Behavior 12%
• Data Preparation 12%
• Road Users 12%
• DeepWalk 12%
• Node2vec 12%
• Network Embedding Method 12%
• Analysis on Graphs 12%
• Feature Network 12%
• Graph Attention Network 12%
• Graph Convolutional Network 12%
• Network Attention 12%
• Model Training 12%
• Moving Behavior 12%

Social Sciences

• Road Network 100%
• Representation Learning 100%
• Travel Time 25%
• Intelligent Transportation System 12%
• Road User 12%
• Data Preparation 12%
• Neural Network 12%
• Graph Convolutional Network 12%