Improving knowledge-aware recommendation with multi-level interactive contrastive learning

• Main Authors: ZOU, Ding, WEI, Wei, WANG, Ziyang, MAO, Xian-Ling, ZHU, Feida, FANG, Rui, CHEN, Dangyang
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2022
• Subjects: Knowledge Graph; Recommendation; Contrastive Learning; Databases and Information Systems
• Online Access: https://ink.library.smu.edu.sg/sis_research/7751; https://ink.library.smu.edu.sg/context/sis_research/article/8754/viewcontent/improving.pdf
• Institution: Singapore Management University

Incorporating Knowledge Graphs (KG) into recommeder system as side information has attracted considerable attention. Recently, the technical trend of Knowledge-aware Recommendation (KGR) is to develop end-to-end models based on graph neural networks (GNNs). However, the extremely sparse user-item in...