Design And Implementation Of Personalized Course Information Management System Based On Collaborative Recommendation Algorithm

Since the Internet is becoming more and more widely used in teaching with the development of modern teaching modes,the online course selection system is playing an important role in educational information management.How to help students select courses according to their interests or needs is becoming one of the highlights in researches on course selection systems.In most of these systems,search engines are used to query course information and select courses.A large number of courses being available,students may not make the right choices easily according to their own needs with the lack of a good knowledge of the courses,thus resulting in a waste of curriculum resources.At present,most of the course selection systems either make no recommendations or use single recommendation technology,which leads to poor recommendation results.Therefore,they can't recommend courses that students may be interested in.However,the personalized course selection system based on collaborative recommendation algorithm which is created according to information such as registration information of students and their curriculum evaluation can solve these problems mentioned to some extent.Firstly,the analysis of the system in the development of the need to follow some of the principles,such as standardization,practicality,advanced.In the development of this system cycle,these principles are applied to the system design and coding stage.And then some of the existing mature technology and framework for a comprehensive comparison,the use of the system SpringMVC technology and MVC design model for development.Secondly,according to the principle of system design,PCIMSCA system design of the overall module,including the system model design,recommended engine model design and database design.The core recommendation module in the system is analyzed in detail,and the recommended technology is described and compared in detail,and some cold start,sparseness and applicability problems based on the content recommendation course algorithm are analyzed.This paper proposes a collaborative recommendation algorithm combining the advantages of multiple recommendation algorithms to compensate for the problem of insufficient single recommendation algorithm,which improves the recommended accuracy rate to a certain extent.Finally,the system functions are implemented and tested.The system implements the function of the recommended course according to the student's behavior record.At the same time,the core recommendation algorithm used in the system is evaluated effectively.The experimental results show that the PCIMSCA system has good recommendation accuracy.