Research And Implementation Of University Information Portal Based On Dubbo And Data Mining

In the present society,information technology has penetrated into all aspects of our life,work,and study.More importantly,information technology has changed our learning style and greatly broadened our knowledge.Based on the construction of university information platform,this paper conducts indepth research on application system integration,data integration and application system development based on data mining and distributed service architecture,and designs and implements Dubbo-based distributed architecture and Apriori's data mining technology.Developed a university information portal based on the concept of distributed services,implemented a unified authentication platform for intra-school portals,implemented singlepoint authentication and cross-system authority authentication,solved the problem of data silos,and fully utilized data value through data mining technology.Though compare and analyze the current mainstream distributed-service architecture,transform the information system with the distributed micro-service architecture,and make implementation plans and steps.Micro-service is to subdivide the individual application according to business,personnel,data,and other dimensions.Each service with unique function,deploys and maintains its own data independently as a single system.Services communicate cooperate with each other through interfaces.With the development of informatization in colleges and universities,a large amount of data is stored in the educational administration system and teaching management system,which records all aspects of students' study and life.Data mining technology is used to process these data intelligently,so as to discover rules and hidden patterns,and form algorithms and services for data collection,processing,analysis and discovery.This can help schools timely understand teaching effects,improve teaching methods,reasonably plan teaching resources,and make students' learning content more personalized by using network teaching platform.Taking Weka data analysis tool as the platform and based on the data collected by the micro-service of teaching and educational administration system,we comb and analyze the student data to realize the personalized optimization recommendation of students' course selection.Use Docker container technology to carry out system deployment,and use existing server hardware and storage resources to minimize capital investment and maximize itseffectiveness.We deployed Nginx cluster,Zookeeper cluster,micro-service cluster,Redis cluster,and My SQL master-slave database.After testing,the system meets the design goal of high concurrency,high performance,and high availability,and is put into formal application,achieving good application results.