Research on the Construction of User Profiles and Personalized Recommendation Models Based on Lifelong Education Data
With the rise of lifelong education,personalized recommendations have become increasingly important in providing learning resources.This paper takes the user data of the"Chaoxuetong"lifelong learning platform in Haining City,Zhejiang Province as the research object,collecting and preprocessing data by constructing a user-learning resource rating matrix.Based on this,through in-depth analysis of user profiling construction and the design of collaborative filtering algorithms,it achieves more accurate personalized learning resource recommendations.
NETL
NSTL
万方数据
