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Ranking User-Generated Content via Multi-Relational Graph C..:
, In:
Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval
,
Narang, Kanika
;
Krishnan, Adit
;
Wang, Junting
... - p. 470-480 , 2021
Link:
https://dl.acm.org/doi/10.1145/3404835.3462857
RT T1 <cTitle>Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval</cTitle>: T1 <Title>Ranking User-Generated Content via Multi-Relational Graph Convolution</Title> UL https://suche.suub.uni-bremen.de/peid=acm-3462857&Exemplar=1&LAN=DE A1 Narang, Kanika A1 Krishnan, Adit A1 Wang, Junting A1 Yang, Chaoqi A1 Sundaram, Hari A1 Sutter, Carolyn PB ACM YR 2021 K1 content ranking K1 graph convolution K1 multi-relational graphs K1 multi-view learning K1 user-generated content K1 Information systems K1 Information retrieval K1 Retrieval models and ranking K1 Learning to rank K1 Users and interactive retrieval K1 Personalization K1 Specialized information retrieval K1 Environment-specific retrieval K1 Web and social media search K1 Retrieval tasks and goals K1 Recommender systems SP 470 OP 480 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3404835.3462857 DO https://dl.acm.org/doi/10.1145/3404835.3462857 SF ELIB - SuUB Bremen
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