Attribute Graph Clustering Based on Self-Supervised Spectral Embedding Network

Attribute graph clustering requires joint modeling of both graph structure and node properties, which is challenging. In recent years, graph neural networks have been utilized to mine deep information on attribute graphs through feature aggregation, learning node embeddings, and using traditional me...

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Detalles Bibliográficos

Autores principales:	Xiaolin Ning, Xueyi Zhao, Yanyun Fu, Guoyang Tang
Formato:	Artigo
Lenguaje:	Inglês
Publicado:	IEEE 2023-01-01
Colección:	IEEE Access
Materias:	Attribute graph clustering self-supervised learning spectral embedding network laplacian smoothing
Acceso en línea:	https://ieeexplore.ieee.org/document/10313268/
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