Design And Implementation Of Expert Manuscript Evaluation System For National Language Commission

The rapid development of technology has made information technology reform an important force for social progress.As the main organization responsible for formulating national language and writing policies,the National Language Commission issued a call for submissions for its journal,"Expert Suggestions from the National Language Commission," which attracted many enthusiastic scholars and experts to submit articles on language,writing,and related fields and hot topics.However,the surge in manuscript numbers has overloaded the early,complex manuscript review process and significantly increased the workload of relevant staff and review experts at the National Language Commission.To address this issue and improve manuscript review efficiency while ensuring fairness and impartiality,the commission needs an information platform to optimize the existing review process and efficiently collect expert data.This paper analyzes the requirements of the National Language Commission in detail,and designs and implements an expert manuscript review system,which includes two core functional modules: manuscript review module and information extraction module.The former includes functions such as multi-process assignment and review,expert and contributor information conflict detection,and message notification to improve the efficiency and fairness of the manuscript review process.The latter involves functions such as expert homepage data collection,topic tag extraction,and portrait construction,making the theme of the manuscript more compatible with expert research directions,and increasing the number of experts in the expert database.The system uses a front-end and back-end separation architecture,with the back-end functions implemented using the Flask framework.The system uses Alibaba Cloud OSS server to store manuscripts,ensuring the security of manuscript storage;Redis,Mysql,and other storage components are used to construct the data access layer to improve data access performance.LDA topic model is used to extract expert tags and accurately obtain expert research directions.The Docker containerization deployment system is used to facilitate the system’s quick migration.The Vue.js framework is used to implement a visual front-end interface,making it easy for users to operate the system.After using the above technologies to complete the system coding,this paper designs functional and non-functional test cases for the entire system,and the final test results meet the expected goals.With the official launch of the expert manuscript review system of the National Language Commission,the core functions of the system have brought great convenience to the management personnel of the Scientific Research Office of the National Language Commission,greatly improving the communication efficiency between users,and ensuring the fairness and impartiality of the review process.In addition,the stability and smoothness of the system have also been demonstrated,and its performance can meet the use needs of staff of the National Language Commission,evaluation experts,and a large number of contributors.In the future,this research will bring certain reference significance to the evaluation system in other fields,and will also contribute to the high-quality development of the national language and writing industry.