Exploration of Personalized Recommendation Method of Agricultural Platform Learning Resources Based on Collaborative Filtering
Due to the lack of consideration of behavioral data between different users in traditional methods,the sat-isfaction with resource recommendations is relatively low.To address this issue,a personalized recommendation method for learning resources on agricultural platforms based on Collaborative Filtering is proposed.This study first introduces Influence Value Parameter-Inf,to represent the size of the influence relationship between different as-sociated users.Then,the sequential comment and reply behavior data are fused to construct an agricultural platform user resource interest matrix.Finally,based on this,Collaborative Filtering method is used to achieve resource rec-ommendation.After testing,it is found that the proposed method has good recommendation performance and can effectively ensure user satisfaction with recommendation resources.
万方数据
维普
