MV-GCN: Multi-View Graph Convolutional Networks for Link Prediction

MV-GCN: Multi-View Graph Convolutional Networks for Link Prediction

Link prediction is a demanding task in real-world scenarios, such as recommender systems, which targets to predict the unobservable links between different objects by learning network-structured data. In this paper, we propose a novel multi-view graph convolutional neural network (MV-GCN) model to s...

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Bibliographic Details
Main Authors: Zhao Li, Zhanlin Liu, Jiaming Huang, Geyu Tang, Yucong Duan, Zhiqiang Zhang, Yifan Yang
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Multi-view
graph convolutional network
link prediction
matrix completion
Online Access:https://ieeexplore.ieee.org/document/8920070/

Internet

https://ieeexplore.ieee.org/document/8920070/

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