Representation learning on multi-layered heterogeneous network
Network data can often be represented in a multi-layered structure with rich semantics. One example is e-commerce data, containing user-user social network layer and item-item context layer, with cross-layer user-item interactions. Given the dual characters of homogeneity within each layer and heter...
Saved in:
Main Authors: | ZHANG, Delvin Ce, LAUW, Hady W. |
---|---|
Format: | text |
Language: | English |
Published: |
Institutional Knowledge at Singapore Management University
2021
|
Subjects: | |
Online Access: | https://ink.library.smu.edu.sg/sis_research/6433 https://ink.library.smu.edu.sg/context/sis_research/article/7436/viewcontent/ecmlpkdd21a.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Singapore Management University |
Language: | English |
Similar Items
-
Meta-learning on heterogeneous information networks for cold-start recommendation
by: LU, Yuanfu, et al.
Published: (2020) -
The 4th workshop on heterogeneous information network analysis and applications (HENA 2021)
by: SHI, Chuan, et al.
Published: (2021) -
Info2vec: an aggregative representation method in multi-layer and heterogeneous networks
by: Yang, Guoli, et al.
Published: (2022) -
Document graph representation learning
by: ZHANG, Ce
Published: (2023) -
Topic-aware heterogeneous graph neural network for link prediction
by: XU, Siyong, et al.
Published: (2021)