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

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 network...

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Bibliographic Details
Main Authors: Mo, Xian, Wan, Binyuan, Tang, Rui, Ding, Junkai, Liu, Guangdi
Format: Article
Published: Wiley 2024
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Online Access:http://eprints.um.edu.my/46062/
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Institution: Universiti Malaya
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