Design Model of Cultural and Creative Products Using User Perception Demand Mining

Area of Science:

• Industrial Design
• Human-Computer Interaction
• Artificial Intelligence

Background:

• Increasing competition necessitates a focus on product design throughout its lifecycle.
• Understanding user emotional needs is crucial for product value and market positioning.
• Traditional methods for measuring user perception are limited in scope and data collection.

Purpose of the Study:

• To propose and validate an artificial intelligence (AI)-driven method for product perceptual design.
• To address limitations in traditional user perceptual cognition measurement.
• To enhance the integration of user emotional needs into the product design process.

Main Methods:

• Development of an AI-driven approach for product perceptual design.
• Utilizing text mining to extract user perceptual cognition from product feedback.
• Demonstrating the method's efficacy through the design of an optometer.

Main Results:

• The AI method effectively extracts user perceptual cognition and emotional needs.
• Text mining provides deeper insights into user expectations compared to traditional methods.
• The designed optometer, based on this method, is more likely to meet user satisfaction.

Conclusions:

• Perceptual design, integrating human and artificial intelligence, increases psychological acceptance and product competitiveness.
• AI-driven analysis of user perception is key to developing user-centric products.
• This approach improves product value by aligning design with user emotional needs.