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Recommender Systems Based on Generative Adversarial Networks: A Problem-Driven Perspective.

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Collaborative Shilling Detection Bridging Factorization and User Embedding., , , , , and . CollaborateCom, volume 252 of Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, page 459-469. Springer, (2017)PUED: A Social Spammer Detection Method Based on PU Learning and Ensemble Learning., , , , , and . CollaborateCom, volume 252 of Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, page 143-152. Springer, (2017)Accelerating Scalable Graph Neural Network Inference with Node-Adaptive Propagation., , , , , , and . CoRR, (2023)Enhancing recommender systems with self-supervised learning. University of Queensland, Australia, (2023)Meta-path Based Heterogeneous Graph Embedding for Music Recommendation., , , and . ICONIP (3), volume 11303 of Lecture Notes in Computer Science, page 101-113. Springer, (2018)Self-Supervised Graph Co-Training for Session-based Recommendation., , , , and . CIKM, page 2180-2190. ACM, (2021)Generating Reliable Friends via Adversarial Training to Improve Social Recommendation., , , , , and . ICDM, page 768-777. IEEE, (2019)Are Graph Augmentations Necessary?: Simple Graph Contrastive Learning for Recommendation., , , , , and . SIGIR, page 1294-1303. ACM, (2022)Motif-based Prompt Learning for Universal Cross-domain Recommendation., , , , and . WSDM, page 257-265. ACM, (2024)Rethinking and Accelerating Graph Condensation: A Training-Free Approach with Class Partition., , , , , , and . CoRR, (2024)