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A multi-view contrastive learning for heterogeneous network embedding

Graph contrastive learning has been developed to learn discriminative node representations on homogeneous graphs. However, it is not clear how to augment the heterogeneous graphs without substantially altering the underlying semantics or how to design appropriate pretext tasks to fully capture the r...

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Detalles Bibliográficos
Autores principales: Li, Qi, Chen, Wenping, Fang, Zhaoxi, Ying, Changtian, Wang, Chen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10130187/
https://www.ncbi.nlm.nih.gov/pubmed/37185784
http://dx.doi.org/10.1038/s41598-023-33324-7