Estimating Network Flowing over Edges by Recursive Network Embedding
In this paper, we propose a novel semisupervised learning framework to learn the flows of edges over a graph. Given the flow values of the labeled edges, the task of this paper is to learn the unknown flow values of the remaining unlabeled edges. To this end, we introduce a value amount hold by each...
Saved in:
Main Authors: | Liqun Yu, Hongqi Wang, Haoran Mo |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2020-01-01
|
Series: | Shock and Vibration |
Online Access: | http://dx.doi.org/10.1155/2020/8893381 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Node and Edge Joint Embedding for Heterogeneous Information Network
by: Lei Chen, et al.
Published: (2024-09-01) -
Recursive Neural Networks Based on PSO for Image Parsing
by: Guo-Rong Cai, et al.
Published: (2013-01-01) -
Network Embedding-Aware Point-of-Interest Recommendation in Location-Based Social Networks
by: Lei Guo, et al.
Published: (2019-01-01) -
A Brief Review of Network Embedding
by: Yaojing Wang, et al.
Published: (2019-03-01) -
Semisupervised Graph Neural Networks for Traffic Classification in Edge Networks
by: Yang Yang, et al.
Published: (2023-01-01)