TransGNN: Harnessing the Collaborative Power of Transformers and Graph Neural Networks for Recommender Systems-Reference-Cited by-同舟云学术

TransGNN: Harnessing the Collaborative Power of Transformers and Graph Neural Networks for Recommender Systems

Published:2024-07-10 Issue: Volume:608 Page:1285-1295
ISSN:
Container-title:Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval
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Author:

Zhang Peiyan¹^ORCID,Yan Yuchen²^ORCID,Zhang Xi³^ORCID,Li Chaozhuo⁴^ORCID,Wang Senzhang⁵^ORCID,Huang Feiran⁶^ORCID,Kim Sunghun¹^ORCID

Affiliation:

1. Hong Kong University of Science and Technology, Hong Kong, Hong Kong

2. School of Intelligence Science and Technology, Peking University, Beijing, China

3. Interdisciplinary Institute for Medical Engineering, Fuzhou University, Fuzhou, China

4. Microsoft Research Asia, Beijing, China

5. Central South University, Changsha, China

6. Jinan University, Guangzhou, China

Funder

Natural Science Foundation of China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3626772.3657721

Reference56 articles.

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5. Chen Cai and Yusu Wang. 2020. A Note on Over-Smoothing for Graph Neural Networks. CoRR , Vol. abs/2006.13318 (2020). showeprint[arXiv]2006.13318 https://arxiv.org/abs/2006.13318