mg2vec: Learning relationship-preserving heterogeneous graph representations via metagraph embedding

• Main Authors: ZHANG, Wentao, FANG, Yuan, LIU, Zemin, WU, Min, ZHANG, Xinming
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2022
• Subjects: heterogeneous information networks; network embedding; relationship mining; Databases and Information Systems
• Online Access: https://ink.library.smu.edu.sg/sis_research/5128; https://ink.library.smu.edu.sg/context/sis_research/article/6131/viewcontent/TKDE20_mg2vec.pdf
• Institution: Singapore Management University

Given that heterogeneous information networks (HIN) encompass nodes and edges belonging to different semantic types, they can model complex data in real-world scenarios. Thus, HIN embedding has received increasing attention, which aims to learn node representations in a low-dimensional space, in ord...