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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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Principais autores: Xiaoli Huang, Jingyu Li, Yumiao Yuan
Format: Artigo
Sprog:Inglês
Udgivet: MDPI AG 2024-05-01
Serier:Entropy
Fag:
link prediction
dynamic social networks
temporal information entropy (TIE)
node2vec
causality analysis
graph convolutional networks (GCNs)
Online adgang:https://www.mdpi.com/1099-4300/26/6/477
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