AAANE: Attention-based Adversarial Autoencoder for Multi-scale Network Embedding

Network embedding represents nodes in a continuous vector space and preserves structure information from the Network. Existing methods usually adopt a “one-size-fits-all” approach when concerning multi-scale structure information, such as first- and second-order proximity of nodes, ignoring the fact that different scales play different roles in the embedding learning.

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Cite this as

Lei Sang, Min Xu, Shengsheng Qian, Xindong Wu (2024). Dataset: AAANE: Attention-based Adversarial Autoencoder for Multi-scale Network Embedding. https://doi.org/10.57702/0ldsfq5z

DOI retrieved: December 2, 2024

Additional Info

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Created December 2, 2024
Last update December 2, 2024
Defined In https://doi.org/10.48550/arXiv.1803.09080
Author Lei Sang
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Min Xu
Shengsheng Qian
Xindong Wu