Design of Multimodal Information Evaluation System Based on Unsupervised Learning

The 21
^st
century is an era of rapid technological development, with increasingly intelligent and personalized means of transmitting, storing, and displaying information. Human communication methods, media, and modes are constantly changing. Human beings can no longer be satisfied with simply communicating information through language or writing, but rather hope to use multiple modes for information reception and transmission. This paper proposed a multimodal information analysis method based on unsupervised learning algorithm. First, it explained and defined the relevant theories of multimodal information and unsupervised learning, and then carried out experimental analysis. The experimental results showed that the efficiency level of multimodal information analysis based on unsupervised learning was higher than that of traditional multimodal information analysis.