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Frontiers of Computer Science

ISSN 2095-2228

ISSN 2095-2236(Online)

CN 10-1014/TP

邮发代号 80-970

2019 Impact Factor: 1.275

Frontiers of Computer Science  2024, Vol. 18 Issue (3): 183343   https://doi.org/10.1007/s11704-024-3803-z
  本期目录
XGCN: a library for large-scale graph neural network recommendations
Xiran SONG1, Hong HUANG1(), Jianxun LIAN2, Hai JIN1
1. National Engineering Research Center for Big Data Technology and System, Services Computing Technology and System Lab, Cluster and Grid Computing Lab, School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China
2. Microsoft Research Asia, Beijing 100080, China
 全文: PDF(875 KB)   HTML
收稿日期: 2023-10-09      出版日期: 2024-03-14
Corresponding Author(s): Hong HUANG   
 引用本文:   
. [J]. Frontiers of Computer Science, 2024, 18(3): 183343.
Xiran SONG, Hong HUANG, Jianxun LIAN, Hai JIN. XGCN: a library for large-scale graph neural network recommendations. Front. Comput. Sci., 2024, 18(3): 183343.
 链接本文:  
https://academic.hep.com.cn/fcs/CN/10.1007/s11704-024-3803-z
https://academic.hep.com.cn/fcs/CN/Y2024/V18/I3/183343
Fig.1  
Fig.2  
Category Models
Pure propagation RandNE
Shallow embedding node2vec, UltraGCN
MP or layer-sampling GraphSAGE, GAT, GIN, LightGCN, SimpleX
Decoupling-based PPRGo, SGC, S2GC, SIGN, GAMLP, GBP
Clustering-based Cluster-GCN
Extreme convolution xGCN
Tab.1  
Datasets: (#nodes, #edges) in million
(0.5, 2.9) (1, 9) (2, 27) (3, 49)
Official 85.1 OOM OOM OOM
RecBole 86.1 813 6591 OOM
XGCN 31.6 248 1825 5462
Tab.2  
1 X, Liu Y, Liu B, Yin H, Yang Z, Luan D Qian . swSpAMM: optimizing large-scale sparse approximate matrix multiplication on Sunway Taihulight. Frontiers of Computer Science, 2023, 17( 4): 174104
2 W, Zhao S, Mu Y, Hou Z, Lin Y, Chen X, Pan K, Li Y, Lu H, Wang C, Tian Y, Min Z, Feng X, Fan X, Chen P, Wang W, Ji Y, Li X, Wang J R Wen . RecBole: towards a unified, comprehensive and efficient framework for recommendation algorithms. In: Proceedings of the 30th ACM International Conference on Information & Knowledge Management. 2021, 4653−4664
3 X, He K, Deng X, Wang Y, Li Y, Zhang M Wang . LightGCN: simplifying and powering graph convolution network for recommendation. In: Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval. 2020, 639−648
4 W, Li M, He Z, Huang X, Wang S, Feng W, Su Y Sun . Graph4Rec: a universal toolkit with graph neural networks for recommender systems. 2023, arXiv preprint arXiv: 2112.01035
5 X, Song J, Lian H, Huang Z, Luo W, Zhou X, Lin M, Wu C, Li X, Xie H Jin . xGCN: an extreme graph convolutional network for large-scale social link prediction. In: Proceedings of the ACM Web Conference 2023. 2023, 349−359
[1] FCS-23803-OF-XS_suppl_1 Download
[2] FCS-23803-OF-XS_suppl_2 Download
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