MOOC Resources Recommendation Based on Heterogeneous Information Network

Aiming at the problem that the existing MOOC recommendation mechanism cannot meet the dynamic and diversified learning needs of different individuals, a MOOC resource recommendation model based on heterogeneous information network is proposed. First by capturing MOOC platform of the heterogeneity between multiple entities in building its corresponding heterogeneous information network, and then through the node level attention and meta-path level fusion of attention, will learn to the user and the knowledge incorporated into the extended matrix factorization framework, to predict user preferences for knowledge, to carry on the personalized recommendation service. Experimental results show that this model has better recommendation performance than other commonly used models, and effectively solves the problem of personalized recommendation for learners.