Neural attention model for recommendation based on factorization machines

In recommendation systems, it is of vital importance to comprehensively consider various aspects of information to make accurate recommendations for users. When the low-order feature interactions between items are insufficient, it is necessary to mine information to learn higher-order feature intera...

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Veröffentlicht in:	Applied intelligence (Dordrecht, Netherlands) Netherlands), 2021-04, Vol.51 (4), p.1829-1844
Hauptverfasser:	Wen, Peng, Yuan, Weihua, Qin, Qianqian, Sang, Sheng, Zhang, Zhijun
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial Intelligence Computer Science Factorization Machines Manufacturing Mechanical Engineering Neural networks Processes Recommender systems
Online-Zugang:	Volltext
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