Design And Implementation Of Learning Management System Based On User Behavior Dynamic Recommendation Algorithm

Along with the rapid development of the Internet and the increasing surge in information,the style of learning and thinking of teachers and students has undergone tremendous changes,and the traditional education model has been unable to satisfy the requirements of teachers and students.The teacher cannot get feedback from the students in time due to his explanation step by step in class,which is likely to cause the incomprehension and strong pressure of students.Existing resources cannot be effectively shared,cannot provide interactive learning,but also cannot provide personalized recommendations based on behavior of user.With the number of students joining the class increasing,the traditional way of learning is subject to the constraints of time and space,simply cannot meet the individual needs of learning.Learning management system is the perfect combination of traditional education and the Internet,through which teaching activities can be more convenient and effective knowledge transfer to the students by the existing classroom teaching methods.The system provides the personalized service,such as search,recommendation,resource reuse.It not only simplifies the workload of teachers,but also provides the function of statistical analysis.Based on the actual situation,the user's behavior is analyzed by the unique recommendation model,and then personalized content will be recommended to the user.Massive data storage and parallel computing are the key and difficult problems in learning management system.For this reason,this paper introduces framework of big data,and designs and implements a comprehensive learning management system.The main work of this thesis is as follows:1)The framework of “SpringMVC + Mysql + Mongodb + Solr + Maven + Redis +Shiro” is used to build the system.Take the curriculum as the core to carry on the expansion,the use of the hierarchical design can carry on the decoupling to the different levels,and reduce the strong dependency.2)Build crawler components,crawl the information of a well-known e-commerce site to access teaching materials.3)Perform a demand analysis of a range of core functions,such as the creation courses,the sets of questions,the composition of test papers and the statistical function.Carry out functional and non-functional design on the core functions.Do the design of database and prototype,then code and do the UI replacement.4)This thesis introduces the framework of big data to solve the problem of storage and parallel computing of massive data.Based on the user behavior log,a large number of literatures are studied,and the recommendation model of the adaptive system is constructed.The recommended model is used to the recommendation of teaching resources for users to improve the intelligent degree of the system,so as to effectively solve a series of issues,for example,the statistical analysis,resource sharing and personalized learning and workload of teacher.