Deep Collaborative Online Learning Resource Recommendation Based on Attention Mechanism

Abstract

In view of the lack of hierarchical and systematic resource recommendation caused by rich online learning resources and many learning platforms, an attention-based ADCF online learning resource recommendation model is proposed by introducing the attention mechanism into a deep collaborative DCF model. Experimental results show that the proposed ADCF model enables an accurate recommendation of online learning resources, reaching 0.626 and 0.339 on the HR and NDCG metrics, respectively, compared to the DCF models before improved, up by 1.31% and 1.25%, and the proposed ADCF models by 1.79%, 2.17%, and 2.32%, respectively, compared to the IUNeu and NeuCF models.