The Research and Implementation of the Automatic Briefing Generation System

This article aims to design and develop a text summarization system utilizing various text language processing models such as Seq2Seq, BERT, TankRank, BART, etc., to enhance the efficiency and accuracy of text processing. By comparing the different characteristics of these models in text processing, it can effectively assist users in generating text summaries. Additionally, the system is built using technologies like Spring Boot, Vue, Uniapp, etc., to provide a user-friendly interface and operational experience. Moreover, the system fully leverages the strengths of Java and Python, integrating them organically to create an intelligent, efficient, and precise automatic briefing generation platform. Users can easily utilize this platform to process large amounts of text information and quickly obtain concise summaries, thereby saving time and improving work efficiency.