Heterogeneous Multi-Behavior Recommendation Based on Graph Convolutional Networks

Traditional recommendation systems usually use single user-item interaction information, which ignore the multiple relationships that exist for other interactions (e.g., likes, clicks). Multi-behavioral recommendation models compensate for the shortcomings of traditional models. The existing multi-b...

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Bibliographic Details

Published in:	IEEE Access
Main Authors:	Ran Rang, Linlin Xing, Longbo Zhang, Hongzhen Cai, Zhaojie Sun
Format:	Article
Language:	English
Published:	IEEE 2023-01-01
Subjects:	Graph convolution networks heterogeneous graph multi-behavior recommendation system
Online Access:	https://ieeexplore.ieee.org/document/10058496/