A multi-intent-aware recommendation algorithm based on interactive graph convolutional networks

In recent years, graph neural networks (GNNs) have been widely applied in recommender systems. However, existing recommendation algorithms based on GNNs still face challenges in node aggregation and feature extraction processes because they often lack the ability to capture the interactions between...

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Veröffentlicht in:	Complex & intelligent systems Jg. 10; H. 3; S. 4493 - 4506
Hauptverfasser:	Zhang, Junsan, Gao, Hui, Xiao, Sen, Zhu, Jie, Wang, Jian
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Cham Springer International Publishing 01.06.2024 Springer Nature B.V Springer
Schlagworte:	Algorithms Artificial neural networks Attention mechanism Collaborative filtering Complexity Computational Intelligence Data Structures and Information Theory Engineering Feature extraction Graph convolutional networks Graph neural networks Original Article Recommender system Recommender systems Attention mechanism Graph convolutional networks Collaborative filtering Recommender system
ISSN:	2199-4536, 2198-6053
Online-Zugang:	Volltext
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