Dynamic Web Page Graphic Design Method for Internet Big Data Information System

Abstract

With the rapid development of the Internet, the page design technology of PC search engine tends to be mature. The content displayed in front of users not only pays attention to the practicability of information, but also takes into account the beauty of page layout. However, the web page design of the Internet mobile terminal is slightly backward, so we study the multimodal method based on the feature of large data density to extract the text, and use the K-means clustering algorithm to classify and recognize the text. The results show that the comprehensive evaluation of the design search engine on multiple platforms is higher than 0.89; In fuzzy keyword retrieval, the average accuracy of dynamic k-value clustering algorithm is 87.5%, while the average accuracy of traditional K-means clustering algorithm is 78.5%. Finally, in terms of user evaluation, the satisfaction of search pages increased by 5%-10%. Experiments show that the optimized algorithm and page design not only improve the accuracy and applicability in function, but also optimize the layout of text and pictures on the page.