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Where to Go Next: Modeling Long- and Short-Term User Preferences for Point-of-Interest Recommendation.

, , , , , and . AAAI, page 214-221. AAAI Press, (2020)

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Collaborative Schema Matching Reconciliation., , , , and . OTM Conferences, volume 8185 of Lecture Notes in Computer Science, page 222-240. Springer, (2013)Hide Your Model: A Parameter Transmission-free Federated Recommender System., , , , , and . CoRR, (2023)Time-aware Dynamic Graph Embedding for Asynchronous Structural Evolution., , , , , , and . CoRR, (2022)Minimizing Efforts in Validating Crowd Answers., , , and . SIGMOD Conference, page 999-1014. ACM, (2015)Completeness and Ambiguity of Schema Cover., , , , , , , , and . OTM Conferences, volume 8185 of Lecture Notes in Computer Science, page 241-258. Springer, (2013)Retaining Data from Streams of Social Platforms with Minimal Regret., , , , and . IJCAI, page 2850-2856. ijcai.org, (2017)Self-Supervised Multi-Channel Hypergraph Convolutional Network for Social Recommendation., , , , , and . WWW, page 413-424. ACM / IW3C2, (2021)Pay-as-you-go reconciliation in schema matching networks., , , , , and . ICDE, page 220-231. IEEE Computer Society, (2014)PipAttack: Poisoning Federated Recommender Systems for Manipulating Item Promotion., , , , , and . WSDM, page 1415-1423. ACM, (2022)Joint Multilingual Knowledge Graph Completion and Alignment., , , , , and . EMNLP (Findings), page 4646-4658. Association for Computational Linguistics, (2022)