Spatial-Temporal Learning-Based Artificial Intelligence for IT Operations in the Edge Network

Keyphrases

• Anomaly Detection 100%
• Learning-based 100%
• Edge Network 100%
• Spatial-temporal Learning 100%
• AIOps 100%
• Operation Staffs 20%
• Key Performance Indicators 20%
• Troubleshooting 20%
• Detection Problem 20%
• Topological Information 20%
• Memory Consumption 20%
• Time Problem 20%
• Spatial-temporal 20%
• Link Delay 20%
• Network Operation 20%
• Graph-based 20%
• Normal Networks 20%
• Root Cause Analysis 20%
• Time Series Data 20%
• Network Scale 20%
• Simulation Platform 20%
• Spatial Dependence 20%
• Graph Convolutional Network 20%
• Detecting Anomalies 20%
• Complex Scenarios 20%
• Intelligent Operation 20%
• Service Interactions 20%
• Software-defined Networking 20%
• Convolutional Encoder 20%
• Anomaly Localization 20%
• Convolutional Layer 20%
• Intelligent Maintenance 20%
• Maintenance Platform 20%
• Operation Platform 20%
• Input Sequence 20%
• Detection Anomaly 20%
• Gated Convolutional Neural Networks 20%

Computer Science

• Anomaly Detection 100%
• Artificial Intelligence 100%
• Software-Defined Networking 40%
• Service Interaction 20%
• Convolutional Network 20%
• Graph Convolutional Network 20%
• Key Performance Indicator 20%
• Detect Anomaly 20%
• Network Operation 20%
• Normal Network 20%
• Anomaly Analysis 20%
• Reconstructed Sequence 20%
• Operation Staff 20%
• Time Series Data 20%
• Experimental Result 20%
• Root Cause Analysis 20%
• Convolutional Layer 20%