Research on the Construction of an Interactive Design Platform Based on Neural Networks and Precision Push Algorithms

Abstract

With the development of the internet, virtual interactive design platforms have gradually emerged. Traditional information carriers have shifted from text and images to multimedia content such as audio and video, and the popularity of social networks has driven new changes in the construction of media platforms. More and more platforms are user-centered, combining big data analysis and personalized recommendations to generate video push systems. This paper uses neural network algorithms to study the construction of interactive design platforms and accurate content pushing. It discusses the information processing issues in interactive design and the reasons behind the popularity of platform-based content push. By utilizing big data analysis and user-centered functions, a video interactive design platform was built, enhancing the visual design effect. The research shows that neural network algorithms can effectively improve the visual design of the platform and provide users with more accurate content recommendations.