Construction of a Visualized Automatic Entry System based on Character Recognition of Foreign Trade English Specific Vocabulary

This article uses the information visualization technology of CiteSpace to analyze the knowledge map of 1106 documents related to international trade semantics in the Web of Science-SSCI core collection from 2008 to 2021, and uses eye tracking technology to restore the dynamic process of vocabulary processing and depth-based information. The learned semantic recognition performs feature recognition and marking on the graph, and the recognition efficiency is increased by 7.6%, and a fully automatic visual input system for international trade proprietary vocabulary is proposed. In the future, it will become a new research method in combination with ERP and other technologies.