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PlatoGL: Effective and Scalable Deep Graph Learning System ..:

, In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management,

Lin, Dandan ; Sun, Shijie ; Ding, Jingtao... - p. 3302-3311 , 2022

Link: https://dl.acm.org/doi/10.1145/3511808.3557084

RT 
T1 <cTitle>Proceedings of the 31st ACM International Conference on Information & Knowledge Management</cTitle>: T1 <Title>PlatoGL: Effective and Scalable Deep Graph Learning System for Graph-enhanced Real-Time Recommendation</Title>

UL https://suche.suub.uni-bremen.de/peid=acm-3557084&Exemplar=1&LAN=DE
				
A1 Lin, Dandan
A1 Sun, Shijie
A1 Ding, Jingtao
A1 Ke, Xuehan
A1 Gu, Hao
A1 Huang, Xing
A1 Song, Chonggang
A1 Zhang, Xuri
A1 Yi, Lingling
A1 Wen, Jie
A1 Chen, Chuan
PB ACM
YR 2022
K1 deep graph learning system
K1 graph neural network
K1 real-time recommendation
K1 Information systems
K1 Information retrieval
K1 Retrieval tasks and goals
K1 Recommender systems
K1 Information systems applications
K1 Data mining
K1 Collaborative filtering
K1 Users and interactive retrieval
K1 Personalization
K1 Data management systems
K1 Database design and models
K1 Graph-based database models
K1 Network data models
SP 3302
OP 3311
LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3511808.3557084
DO https://dl.acm.org/doi/10.1145/3511808.3557084
SF ELIB - SuUB Bremen

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