Attribute imputation autoencoders for attribute-missing graphs

Analyzing attribute-missing graphs with a complete topology, but missing the attributes of some nodes, is an emerging and challenging research topic. Data imputation techniques based on graph autoencoders are commonly used for attribute-missing graphs. However, this method cannot effectively integra...

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Bibliographic Details

Published in:	Knowledge-based systems Vol. 291; p. 111583
Main Authors:	Xia, Riting, Zhang, Chunxu, Li, Anchen, Liu, Xueyan, Yang, Bo
Format:	Journal Article
Language:	English
Published:	Elsevier B.V 12.05.2024
Subjects:	Attribute-missing graphs Data imputation Generative ability Graph autoencoder Robustness Graph autoencoder Robustness Data imputation Generative ability Attribute-missing graphs
ISSN:	0950-7051, 1872-7409
Online Access:	Get full text
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