Combining user-end and item-end knowledge graph learning for personalized recommendation

How to accurately model user preferences based on historical user behaviour and auxiliary information is of great importance in personalized recommendation tasks. Among all types of auxiliary information, knowledge graphs (KGs) are an emerging type of auxiliary information with nodes and edges that...

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Veröffentlicht in:	Journal of intelligent & fuzzy systems 2021-01, Vol.40 (5), p.9213-9225
Hauptverfasser:	Gu, Tianlong, Liang, Haohong, Bin, Chenzhong, Chang, Liang
Format:	Artikel
Sprache:	eng
Schlagworte:	Convolution Customization Embedding Knowledge representation Learning Multilayers Semantics User behavior
Online-Zugang:	Volltext
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