HAKG: Hierarchy-Aware Knowledge Gated Network for Recommendation
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 information propagation mechanism. However, existing propagationbased methods fail to (1) model the underlying hi...
Saved in:
Main Authors: | DU, Yuntao, ZHU, Xinjun, CHEN, Lu, ZHENG, Baihua, GAO, Yunjun |
---|---|
格式: | text |
語言: | English |
出版: |
Institutional Knowledge at Singapore Management University
2022
|
主題: | |
在線閱讀: | https://ink.library.smu.edu.sg/sis_research/7181 https://ink.library.smu.edu.sg/context/sis_research/article/8184/viewcontent/_Submit__HAKG__Hierarchy_Aware_Knowledge_Gated_Network_for_Recommendation.pdf |
標簽: |
添加標簽
沒有標簽, 成為第一個標記此記錄!
|
相似書籍
-
Multi-level cross-view contrastive learning for knowledge-aware recommender system
由: ZOU, Ding, et al.
出版: (2022) -
Knowledge enhanced multi-intent transformer network for recommendation
由: ZOU, Ding, et al.
出版: (2024) -
Improving knowledge-aware recommendation with multi-level interactive contrastive learning
由: ZOU, Ding, et al.
出版: (2022) -
Multi-level cross-view contrastive learning for knowledge-aware recommender system
由: ZOU, Ding, et al.
出版: (2022) -
Learning and Reasoning on Graph for Recommendation
由: Xiang Wang, et al.
出版: (2020)