Construction of a Personalized Recommendation Model for MOOC Courses Based on LGAT

Massive Online Open Class (MOOC) has developed rapidly in recent years, with a large number of learners and a platform that records students’ learning data in detail. How to recommend MOOC courses effectively is of great significance. Graph Attention Network (GAT) uses attention mechanisms for feature aggregation on graph data, which is of great significance for recommending graph data. This article applies GAT for recommendation research based on the relationship between information in MOOC and graph data features. And the reliability of the method was verified experimentally.