Graph-Based Feature Crossing to Enhance Recommender Systems

In recommendation tasks, most existing models that learn users’ preferences from user–item interactions ignore the relationships between items. Additionally, ensuring that the crossed features capture both global graph structures and local context is non-trivial, requiring innovative techniques for...

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Bibliographic Details
Main Authors:	Congyu Cai, Hong Chen, Yunxuan Liu, Daoquan Chen, Xiuze Zhou, Yuanguo Lin
Format:	Article
Language:	English
Published:	MDPI AG 2025-01-01
Series:	Mathematics
Subjects:	recommender systems convolutional neural network graph neural network co-occurrence pattern transformer model
Online Access:	https://www.mdpi.com/2227-7390/13/2/302
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Graph-Based Feature Crossing to Enhance Recommender Systems

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