Multi-modal e-commerce data analysis system based on deep learning: visual perception and emotional computing

Key Points

• This research aims to create a system that analyzes e-commerce data using deep learning techniques to improve visual understanding and emotional interpretation.
• Developed a multi-modal data analysis system utilizing deep learning algorithms.
• Incorporated emotional computing and visual perception algorithms into the system.
• Analyzed how these modalities improve the interpretation of e-commerce data.
• The system significantly enhances data insights related to customer emotions and perceptions.
• Visual perception algorithms increase data interpretation accuracy by 30% (p<0.05).
• Emotional computing improves user engagement metrics by 25%.

Abstract