Deep Attributed Network Embedding via Weisfeiler-Lehman and Autoencoder
Author:
Affiliation:
1. Computer Science Department, Ibb University, Ibb, Yemen
2. Computer Science Department, Faculty of Computers and Information, Mansoura University, Mansoura, Egypt
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/6287639/9668973/09791249.pdf?arnumber=9791249
Reference54 articles.
1. Deep attributed network representation learning via attribute enhanced neighborhood;li;arXiv 2104 05234,2021
2. From Properties to Links
3. Discrete Embedding for Latent Networks
4. Weisfeiler-Lehman graph kernels;shervashidze;J Mach Learn Res,2011
5. Learning Deep Network Representations with Adversarially Regularized Autoencoders
Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Attributed Network Embedding Using an Improved Weisfeiler-Lehman Schema and a Novel Deep Skip-Gram;IEEE Access;2023
2. Auto-encoder and Graph Neural Networks-Based Hybrid Model for Link Prediction on Complex Network;Intelligent Computing and Networking;2023
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