Application Of PageRank Algorithm Based On Hadoop In Teaching Knowledge Point Analysis Of Network Course

With the continuous progress of information technology,online courses are more and more popular.Because of its flexibility,openness,and universality,it has attracted many learners once it came out.It can be said that the emergence of online courses has broken the traditional teaching model.However,as more and more people are engaged in the study of online courses,the problems of lenient entry,strict exit,low completion rate,and insufficient teaching guidance have gradually emerged.The reason behind this is often because online courses cannot achieve personalized and differentiated teaching,and cannot stimulate the subjective initiative of learners,leading to the problem of unsatisfactory learning results.Throughout the existing online teaching platforms,the current importance of knowledge points often comes from the teaching experience of experts and scholars.Through simple knowledge map construction,it is presented to learners in the form of directory structure and mind map.However,such a fixed sort of knowledge points generated based on experience can no longer meet the needs of learners of online courses.Learners cannot quickly locate the importance of the current learning content in massive knowledge according to their own situation,thereby reducing the learners' Learning efficiency reduces learning interest.In order to maximize the subjective ability of learners,reduce the barriers between learners and websites,reduce the cost of interaction,and scientifically and effectively sort the discrete knowledge points,this article references the PageRank algorithm to disciplinary knowledge points.Scoring was explored.The article first discusses the current application status of online teaching courses,Hadoop platforms,and PageRank algorithm in China,and analyzes the problems of online teaching and adoption technology in the current environment.Based on the current problems and the characteristics of the knowledge demand of online course learning users,the concept of "score knowledge points" is proposed,and the application of PageRank algorithm based on Hadoop platform to the knowledge points score of online courses is discussed.By designing corresponding research methods and research contents,the theoretical support and technical support of knowledge point analysis of network teaching are fully demonstrated.The feasibility of scoring Hadoop platform and PageRank algorithm in scoring the knowledge points of online course teaching is analyzed,and it is realized through simulation experiments.