Link prediction on latent heterogeneous graphs

Link prediction on latent heterogeneous graphs

On graph data, the multitude of node or edge types gives rise to heterogeneous information networks (HINs). To preserve the heterogeneous semantics on HINs, the rich node/edge types become a cornerstone of HIN representation learning. However, in real-world scenarios, type information is often noisy...

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書目詳細資料
Main Authors:	NGUYEN, Trung Kien, LIU, Zemin, FANG, Yuan
格式:	text
語言:	English
出版:	Institutional Knowledge at Singapore Management University 2023
主題:	Latent heterogeneous graph Link prediction Graph neural networks Databases and Information Systems OS and Networks
在線閱讀:	https://ink.library.smu.edu.sg/sis_research/8190 https://ink.library.smu.edu.sg/context/sis_research/article/9193/viewcontent/3543507.3583284_pvoa_cc_by.pdf
標簽:	添加標簽沒有標簽, 成為第一個標記此記錄!
機構:	Singapore Management University
語言:	English

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