arrow
Return

CMC-GCN: Consistent multi-granularity cascading graph convolution network for multi-behavior recommendation

delete2025-07-08
delete0
PRE
AI
Y
Yabo Yin
X
Xiaofei Zhu *
K
Kunyang Huang
W
Wenshan Wang
张宜浩 (Yihao Zhang)
P
Pengfei Wang
Y
Yixing Fan
J
Jiafeng Guo
DOI:10.1016/j.neucom.2025.130952delete
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

En 中文
• Introduce a novel multi-granularity cascading graph convolutional network. • Propose a behavior consistency-guided alignment strategy to maintain both intra- and inter-behavior consistency. • Conduct extensive experiments on four real-world datasets to examine model’s effectiveness.
Keywords:
multi-granularity
cascading graph convolutional network
behavior consistency
alignment strategy
real-world datasets

Journal

Neurocomputing cover
Neurocomputing
IF:
6.5
Papers:
2.5W
Citations:
6.5W

Organization

B
Beijing University of Posts and Telecommunications
Scholars:
2.6K
Papers: 1.2K
Citations: 4.2K
W
Wenzhou-Kean University
Scholars:
664
Papers: 593
Citations: 610
C
Chongqing University of Technology
Scholars:
5.8K
Papers: 3.5K
Citations: 3
C
chinese academy of sciences
Scholars:
56.0W
Papers: 44.8W
Citations: 704
researcher View more organizations