Metagraph-based learning on heterogeneous graphs
Data in the form of graphs are prevalent, ranging from biological and social networks to citation graphs and the Web. Inparticular, most real-world graphs are heterogeneous, containing objects of multiple types, which present new opportunities for manyproblems on graphs. Consider a typical proximity...
Saved in:
Main Authors: | FANG, Yuan, LIN, Wenqing, ZHENG, Vincent W., WU, Min, SHI, Jiaqi, CHANG, Kevin, LI, Xiao-Li |
---|---|
Format: | text |
Language: | English |
Published: |
Institutional Knowledge at Singapore Management University
2019
|
Subjects: | |
Online Access: | https://ink.library.smu.edu.sg/sis_research/4726 https://ink.library.smu.edu.sg/context/sis_research/article/5729/viewcontent/TKDE19_MG.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Singapore Management University |
Language: | English |
Similar Items
-
Heterogeneous graph transformer with poly-tokenization
by: LU, Zhiyuan, et al.
Published: (2024) -
Topic-aware heterogeneous graph neural network for link prediction
by: XU, Siyong, et al.
Published: (2021) -
Learning on heterogeneous graphs using high-order relations
by: Lee, See Hian, et al.
Published: (2021) -
The 4th workshop on heterogeneous information network analysis and applications (HENA 2021)
by: SHI, Chuan, et al.
Published: (2021) -
Dynamic heterogeneous graph embedding via heterogeneous Hawkes process
by: JI, Yugang, et al.
Published: (2021)