Interactive Visual Communication Design of Mobile App Interface Based on Artificial Intelligence Technology

Abstract

Mobile app interface design is a crucial aspect of human-computer interaction. Interactive mobile app interface design becomes even more important. However, the traditional design system based on convolutional neural networks (CNN) has low accuracy and poor effect. It is important to improve the system to enhance user experience. To address these issues, the study utilizes the K-means clustering (KMC) algorithm and principal component analysis to analyze the collected user data for demand analysis. Then, a deep adversarial CNN is employed to generate a design scheme for the interactive mobile cell phone application. After evaluation by several mobile front-end engineers, the system designed products with an average rating of 85 for aesthetics, 89 for ease of use, and 83 for information intuitiveness. These excellent results highlight the method’s supremacy in interface design aesthetics and user experience, as well as its effectiveness and clarity in information organization and presentation.