Heterogeneous graph representation learning and applications
Representation learning in heterogeneous graphs (HG) is intended to provide a meaningful vector representation for each node so as to facilitate downstream applications such as link prediction, personalized recommendation, node classification, etc. This task, however, is challenging not only because...
| Main Author: | Shi, Chuan, |
|---|---|
| Other Authors: | Wang, Xiao, 1987-, Yu, Philip S.,, SpringerLink (Online service) |
| Format: | eBook |
| Language: | English |
| Published: |
Singapore :
Springer,
2021.
Singapore : 2021. |
| Physical Description: |
1 online resource. |
| Series: |
Artificial intelligence: foundations, theory, and algorithms,.
|
| Subjects: |
CMU Electronic Access
Electronic Resource Click Here| Location | Call Number: | Status |
|---|---|---|
| CMU Electronic Access | Available |