Deep Attributed Network Embedding via Weisfeiler-Lehman and Autoencoder

Deep Attributed Network Embedding via Weisfeiler-Lehman and Autoencoder

Network embedding plays a critical role in many applications. Node classification, link prediction, and network visualization are examples of such applications. Attributed network embedding aims to learn the low-dimensional representation of network nodes by integrating network architecture and attr...

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Bibliographic Details
Main Authors: Amr Thabit Al-Furas, Mohammed F. Alrahmawy, Waleed Mohamed Al-Adrousy, Samir Elmougy
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Attributed network embedding
autoencoder
link prediction
node classification
visualization
Weisfeiler-Lehman proximity schema
Online Access:https://ieeexplore.ieee.org/document/9791249/

Internet

https://ieeexplore.ieee.org/document/9791249/

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