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A Survey of Graph Neural Networks for Recommender Systems: Challenges, Methods, and Directions

📅 January 14, 2023 👤 Chen Gao, Yu Zheng, Nian Li et al. 📖 ACM Transactions on Recommender Systems 📊 660 citations

🤖 Plain-English Summary

Recommender system is one of the most important information services on today’s Internet. Finally, we raise discussions on the open problems and promising future directions in this area.

🔑 Key Findings

  • Recently, graph neural networks have become the new advanced approach to recommender systems.
  • In this survey, we conduct a comprehensive review of the literature on graph neural network-based recommender systems.
  • We first introduce the background and the history of the development of both recommender systems and graph neural networks.

💡 Why This Matters

This research advances how AI systems learn, reason, and solve problems — with direct implications for automation and scientific discovery.

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📋 Article Details

Category 🤖 Artificial Intelligence
Published Jan 14, 2023
Journal ACM Transactions on Recommender Systems
Authors Chen Gao, Yu Zheng, Nian Li, Yinfeng Li, Yingrong Qin
DOI 10.1145/3568022
Citations 660
Source OpenAlex

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