Attention‐based network embedding with higher‐order weights and node attributes

Attention‐based network embedding with higher‐order weights and node attributes

Abstract Network embedding aspires to learn a low‐dimensional vector of each node in networks, which can apply to diverse data mining tasks. In real‐life, many networks include rich attributes and temporal information. However, most existing embedding approaches ignore either temporal information or...

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Bibliographic Details
Main Authors: Xian Mo, Binyuan Wan, Rui Tang, Junkai Ding, Guangdi Liu
Format: Article
Language:English
Published: Wiley 2024-04-01
Series:CAAI Transactions on Intelligence Technology
Subjects:
data mining
deep neural networks
social network
Online Access:https://doi.org/10.1049/cit2.12215

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