Artificial Intelligence-Based Human–Computer Interaction Technology Applied in Consumer Behavior Analysis and Experiential Education - Li, Yanmin; Zhong, Ziqi; Zhang, Fengrui; Zhao, Xinjie (Frontiers in Psychology, 2022)
In the course of consumer behaviour, it is necessary to study the relationship between the characteristics of psychological activities and the laws of behaviour when consumers acquire and use products or services. With the development of the Internet and mobile terminals, electronic commerce (E-commerce) has become an important form of consumption for people. In order to conduct experiential education in E-commerce combined with consumer behaviour courses to understand consumer satisfaction. From the perspective of E-commerce companies, this work proposes to use artificial intelligence (AI) image recognition technology to recognize and analyse consumer facial expressions. First, it analyses the way of Human Computer Interaction (HCI) in the context of E-commerce, and obtains consumer satisfaction with the product through HCI technology. Then, deep neural network (DNN) is used to predict the psychological behaviour and consumer psychology of consumers to realize personalized product recommendation. In the course education of consumer behaviour, it helps to understand consumer satisfaction and make reasonable design. The experimental results show that consumers are highly satisfied with the products recommended by the system, and the degree of sanctification reaches 93.2%. It is found that the DNN model can learn consumer behaviour rules during evaluation, and its prediction effect is increased by 10% compared with the traditional model, which confirms the effectiveness of the recommendation system under the DNN model. This work provides a reference for consumer psychological behaviour analysis based on HCI in the context of AI, which is of great significance to help understand consumer satisfaction in consumer behaviour education in the context of E-commerce.