Macro Graph Neural Networks for Online Billion-Scale Recommender Systems-Reference-Cited by-同舟云学术

Macro Graph Neural Networks for Online Billion-Scale Recommender Systems

Published:2024-05-13 Issue: Volume: Page:3598-3608
ISSN:
Container-title:Proceedings of the ACM Web Conference 2024
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Author:

Chen Hao¹^ORCID,Bei Yuanchen²^ORCID,Shen Qijie³^ORCID,Xu Yue³^ORCID,Zhou Sheng²^ORCID,Huang Wenbing⁴^ORCID,Huang Feiran⁵^ORCID,Wang Senzhang⁶^ORCID,Huang Xiao¹^ORCID

Affiliation:

1. The Hong Kong Polytechnic University, Hung Hom, Hong Kong

2. Zhejiang University, Hangzhou, China

3. Alibaba Group, Hangzhou, China

4. Renmin University of China, Beijing, China

5. Jinan University, Guangzhou, China

6. Central South University, Changsha, China

Funder

the National Natural Science Foundation of China

the Scientific Innovation 2030 Major Project for New Generation of AI, Ministry of Science and Technology of the People?s Republic of China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3589334.3645517

Reference43 articles.

1. Non-Recursive Cluster-Scale Graph Interacted Model for Click-Through Rate Prediction

2. Yuanchen Bei, Sheng Zhou, Qiaoyu Tan, Hao Xu, Hao Chen, Zhao Li, and Jiajun Bu. 2023 b. Reinforcement Neighborhood Selection for Unsupervised Graph Anomaly Detection. In 2023 IEEE International Conference on Data Mining (ICDM).

3. Sampling Is All You Need on Modeling Long-Term User Behaviors for CTR Prediction

4. Non-Recursive Graph Convolutional Networks

5. Generative Adversarial Framework for Cold-Start Item Recommendation

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