An Information-Explainable Random Walk Based Unsupervised Network Representation Learning Framework on Node Classification Tasks

An Information-Explainable Random Walk Based Unsupervised Network Representation Learning Framework on Node Classification Tasks

Network representation learning aims to learn low-dimensional, compressible, and distributed representational vectors of nodes in networks. Due to the expensive costs of obtaining label information of nodes in networks, many unsupervised network representation learning methods have been proposed, wh...

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Bibliographic Details
Main Authors: Xin Xu, Yang Lu, Yupeng Zhou, Zhiguo Fu, Yanjie Fu, Minghao Yin
Format: Article
Language:English
Published: MDPI AG 2021-07-01
Series:Mathematics
Subjects:
network representation learning
random walk
stationary distributions
unsupervised learning
network embedding
Online Access:https://www.mdpi.com/2227-7390/9/15/1767

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https://www.mdpi.com/2227-7390/9/15/1767

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