Yijun Su — accepted AI-conference papers

2024

Adaptive Spatial-Temporal Hypergraph Fusion Learning for Next POI Recommendation

Yantong Lai, Yijun Su, Lingwei Wei, Tianci Wang, Daren Zha, Xin Wang

ICASSP 2024accepted

Next point-of-interest (POI) recommendation has been a trending task to provide next POI suggestions. Most existing sequential-based and graph-based methods have endeavored to model user visiting behaviors and achieved considerable performances. However, they have either modeled user interests at a…

Cited by 0 Source ↗Scholar ↗

2023

Win-Win: A Privacy-Preserving Federated Framework for Dual-Target Cross-Domain Recommendation

Gaode Chen, Xinghua Zhang, Yijun Su, Yantong Lai, Ji Xiang, Junbo Zhang +1

AAAI 2023technical

Cross-domain recommendation (CDR) aims to alleviate the data sparsity by transferring knowledge from an informative source domain to the target domain, which inevitably proposes stern challenges to data privacy and transferability during the transfer process. A small amount of recent CDR works have…

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