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Related Experiment Videos

Artificial Intelligence-Based Human-Computer Interaction Technology Applied in Consumer Behavior Analysis and

Yanmin Li¹, Ziqi Zhong², Fengrui Zhang³

¹Pan Tianshou College of Architecture, Art and Design, Ningbo University, Ningbo, China.

Frontiers in Psychology

|April 25, 2022

Summary

This summary is machine-generated.

Artificial intelligence (AI) analyzes consumer facial expressions via human-computer interaction (HCI) in e-commerce. A deep neural network (DNN) model enhances personalized recommendations, achieving 93.2% consumer satisfaction.

Keywords:

behavior analysis customer psychology deep neutral network human-computer interaction image recognition

Related Experiment Videos

Area of Science:

Consumer Behavior Analysis
Artificial Intelligence Applications
Human-Computer Interaction

Background:

E-commerce is a significant consumption channel, necessitating understanding consumer behavior and satisfaction.
Experiential education in e-commerce requires effective methods to gauge consumer satisfaction.
Analyzing psychological activities and behavioral patterns is crucial for consumer acquisition and product usage.

Purpose of the Study:

To propose and evaluate the use of AI image recognition for analyzing consumer facial expressions in e-commerce.
To leverage human-computer interaction (HCI) to assess consumer satisfaction with products.
To employ a deep neural network (DNN) for predicting consumer psychology and enabling personalized recommendations.

Main Methods:

Utilizing AI image recognition to analyze consumer facial expressions during e-commerce interactions.
Applying HCI techniques to capture and interpret consumer satisfaction signals.
Developing and implementing a DNN model for psychological behavior prediction and personalized product suggestions.

Main Results:

The AI-driven recommendation system achieved a high consumer satisfaction rate of 93.2%.
The DNN model demonstrated improved learning of consumer behavior rules compared to traditional models.
The DNN model's prediction accuracy showed a 10% increase over conventional methods.

Conclusions:

AI-powered analysis of facial expressions through HCI offers valuable insights into consumer satisfaction in e-commerce.
The DNN model effectively predicts consumer behavior, enhancing personalized recommendations and educational design.
This research provides a significant reference for AI-based consumer psychological analysis in e-commerce education.