Automatic prediction of tourist travel trajectory using joint graph convolutional neural network

Key Points

• The goal is to automatically predict the travel trajectory of tourists using advanced neural network techniques.
• Utilized a joint graph convolutional neural network to analyze travel data.
• Designed experiments with varying parameters to test prediction accuracy.
• Evaluated performance against traditional methods.
• Achieved a significant increase in prediction accuracy compared to conventional algorithms.
• Demonstrated the model's effectiveness in real-world tourist scenarios.
• Highlighted potential applications in travel planning and tourism management.