Research of Course Resource Recommendation Technology Based on Deep Learning
With the development of the Internet,Internet plus is constantly changing our tradi-tional industries,as is the education industry.Driven by the online education mode of Internet plus education,the use of various digital tools has also accelerated the digital transformation of schools.The learning mode of learners is no longer limited to traditional offline learning,and various online courses are also recognized and loved by everyone,and various online education platforms are gradually being promoted.The online education platform has the characteristics of rich course resources and real-time online learning,which has been favored by many learners.But with the exponential increase of course resources,learners find it difficult to find suitable courses from numerous courses.In order to improve user stickiness,education platforms have al-so introduced recommendation algorithms.In traditional recommendation algorithms,the com-monly used one is the collaborative filtering recommendation algorithm,which can improve the accuracy of recommendations to a certain extent.However,collaborative filtering recommenda-tion algorithms also face the problems of cold start and sparse data.In order to solve this prob-lem,this project introduces a neural network method based on deep learning,which combines deep learning and collaborative filtering to further improve the accuracy of course resource rec-ommendations on online platforms.
Deep learningCourse recommendationsPersonalized learningOnline education
NETL
NSTL
万方数据
