Online Learning Recommendation Platform Based On Spring Cloud And Course Characteristic Attributes

With the popularization of the Internet,coupled with the guidance of various government policies and the influx of capital into the education industry,online education has gradually emerged.However,due to the limitations of the technology at the time,the traditional online learning platform was developed with a monolithic architecture,which had problems such as low flexibility,poor scalability,and poor stability,and could not meet the growing business scale and User needs.Moreover,the traditional ranking recommendation algorithm also has the problem of credibility of small samples and the Matthew effect.In order to solve the above problems,this paper designs and implements an online learning recommendation platform based on Spring Cloud and course characteristic attributes.The platform has certain application value.The specific work content is as follows:First of all,by analyzing the traditional online learning platform,it was found that it had problems such as low flexibility,scalability,and poor stability.Microservices could just solve the above pain points.Therefore,it was determined to use the microservice architecture to develop the online learning recommendations of this article.platform.Secondly,based on the concept of microservice architecture,the current popular microservice framework Spring Cloud is used for development.Strictly follow the scientific software development process,first feasibility analysis and demand analysis of the online learning recommendation platform are conducted,and at the same time the overall architecture of the platform is designed;then,based on the analysis of platform function requirements,the platform Microservice module is designed according to system functions;finally the database of the platform is designed.Then,it is aimed at the small sample credibility problem and Matthew effect existing in traditional ranking recommendation algorithms.The positive rate and the total evaluation number of the course characteristic attributes are analyzed and extracted,combined with Wilson interval and time decay function.A sorting recommendation algorithm based on the course characteristic attributes is proposed.Finally,the current popular Java Web development technologies and tools such as Spring Cloud,Vue.js and IntelliJ IDEA are selected to implement the front-end and back-end system of the online learning recommendation platform,and the ranking recommendation algorithm based on the characteristics of the course is implemented on the platform.,And test the platform and ranking recommendation algorithm at the same time.The test results show that the platform is flexible to deploy,easy to expand,and stable in use.Users can quickly access and use system functions on multiple browsers,improve the credibility of small samples,and alleviate the Matthew effect,and can be more accurate Recommend course resources to users in a non-personal ized way.