Review on heterogeneous network representation learning method
Most of the real-life networks are heterogeneous networks that contain multiple types of nodes and edges, and heterogeneous networks integrate more information and contain richer semantic information than homogeneous networks. Heterogeneous network representation learning to have powerful modeling c...
Main Authors: | Jianxia WANG, Menglin LIU, Yunfeng XU, Yan ZHANG |
---|---|
Format: | Article |
Language: | zho |
Published: |
Hebei University of Science and Technology
2021-02-01
|
Series: | Journal of Hebei University of Science and Technology |
Subjects: | |
Online Access: | http://xuebao.hebust.edu.cn/hbkjdx/ch/reader/create_pdf.aspx?file_no=b202101007&flag=1&journal_ |
Similar Items
-
A Semantic Aware Meta-Path Model for Heterogeneous Network Representation Learning
by: Yiping Yang, et al.
Published: (2020-01-01) -
A survey of information network representation learning
by: Junhao LU, et al.
Published: (2020-04-01) -
Towards Robust Representations of Spatial Networks Using Graph Neural Networks
by: Chidubem Iddianozie, et al.
Published: (2021-07-01) -
SR-HGAT: Symmetric Relations Based Heterogeneous Graph Attention Network
by: Zhenghao Zhang, et al.
Published: (2020-01-01) -
An End-to-End Multiplex Graph Neural Network for Graph Representation Learning
by: Yanyan Liang, et al.
Published: (2021-01-01)