HybridGNN: Learning Hybrid Representation in Multiplex Heterogeneous Networks

Recently, graph neural networks have shown the superiority of modeling the complex topological structures in heterogeneous network-based recommender systems. Due to the diverse interactions among nodes and abundant semantics emerging from diverse types of nodes and edges, there is a bursting researc...

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Veröffentlicht in:	arXiv.org 2022-08
Hauptverfasser:	Gu, Tiankai, Wang, Chaokun, Wu, Cheng, Xu, Jingcao, Yunkai Lou, Wang, Changping, Xu, Kai, Ye, Can, Yang, Song
Format:	Artikel
Sprache:	eng
Schlagworte:	Agglomeration Graph neural networks Heterogeneity Learning Modules Multiplexing Nodes Recommender systems Representations Semantics
Online-Zugang:	Volltext
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