HAKG
Yuntao Du, Xinjun Zhu, Lu Chen, Baihua Zheng, Yunjun Gao
2022Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval49 citationsDOI
Abstract
Knowledge graph (KG) plays an increasingly important role to improve the recommendation performance and interpretability. A recent technical trend is to design end-to-end models based on the information propagation schemes. However, existing propagation-based methods fail to (1) model the underlying hierarchical structures and relations, and (2) capture the high-order collaborative signals of items for learning high-quality user and item representations.
Topics & Concepts
InterpretabilityComputer scienceGraphKnowledge graphArtificial intelligenceTheoretical computer scienceInformation retrievalRecommender Systems and TechniquesAdvanced Graph Neural NetworksTopic Modeling