IcaGCN: Model Intents via Coactivated Graph Convolution Network for Recommendation

IcaGCN: Model Intents via Coactivated Graph Convolution Network for Recommendation

In this era of information overload, to better provide personalized content services to users, recommendation systems have greatly improved the efficiency of information distribution. Graph Convolution Network(GCN), which is one of the representative works of graph structure aggregation processing,...

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Bibliographic Details
Main Authors: Jingxue Zhang, Changchun Yang
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
Recommender systems
graph neural networks
collaborative filtering
Online Access:https://ieeexplore.ieee.org/document/10105951/

Internet

https://ieeexplore.ieee.org/document/10105951/

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