Application of Personalized Recommendation Technology in MOOC System
Zhao Xu, Bingyue Liu · 2020
In order to solve the problem that it is difficult for users to retrieve information and the retrieval results are inaccurate, this paper proposes a personalized recommendation algorithm based on user collaborative filtering applied to MOOC system. First of all, the system forms the user interest model vector by collecting the user's behavior log and analyzing it. Secondly, the label is created for each resource of the system, and the user's score of the resource is collected in the process of user use. Finally, on the basis of the user interest model and resource characteristics, combined with the personalized recommendation algorithm, the resources that meet the user's requirements are recommended to the target user. The system test results show that the users are highly satisfied with the recommendation results of the system, and the application of personalized recommendation algorithm in MOOC system can provide users with more effective information and resources.