Link Prediction in Dynamic Social Networks Combining Entropy, Causality, and a Graph Convolutional Network Model

Link prediction is recognized as a crucial means to analyze dynamic social networks, revealing the principles of social relationship evolution. However, the complex topology and temporal evolution characteristics of dynamic social networks pose significant research challenges. This study introduces...

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Detalhes bibliográficos

Principais autores:	Xiaoli Huang, Jingyu Li, Yumiao Yuan
Formato:	Artigo
Idioma:	Inglês
Publicado em:	MDPI AG 2024-05-01
coleção:	Entropy
Assuntos:	link prediction dynamic social networks temporal information entropy (TIE) node2vec causality analysis graph convolutional networks (GCNs)
Acesso em linha:	https://www.mdpi.com/1099-4300/26/6/477
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