A Course Recommendation Method Based on the Integration of Curriculum Knowledge Graph and Collaborative Filtering

• Published in: International journal of advanced network, monitoring, and controls Vol. 10; no. 2; pp. 94 - 100
• Main Authors: Hu, Jingyi, Wang, Qingqing
• Format: Journal Article
• Language: English
• Published: Xi'an Sciendo 16.06.2025; De Gruyter Poland
• Subjects: Accuracy; Algorithms; Collaboration; Core curriculum; Course Attributes; Data mining; Data Sparsity; Datasets; Graphs; Information sources; Knowledge Graph; Knowledge representation; Learning; Propagation; Ratings & rankings; Recommender systems; Semantics; Students
• ISSN: 2470-8038; 2470-8038
• DOI: 10.2478/ijanmc-2025-0020

To address the problems of data sparsity and cold start in collaborative filtering algorithms, this paper proposes an improved course recommendation method that integrates knowledge graphs and collaborative filtering. First, the RippleNet model is used to construct a knowledge graph based on course-...