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Exploiting uninteresting items for effective graph-based one-class collaborative filtering., , , , and . J. Supercomput., 77 (7): 6832-6851 (2021)Towards Fair Graph Anomaly Detection: Problem, New Datasets, and Evaluation., , , , and . CoRR, (2024)AiRS: A Large-Scale Recommender System at NAVER News., , , , , , , , , and 9 other author(s). ICDE, page 3386-3398. IEEE, (2022)THOR: Self-Supervised Temporal Knowledge Graph Embedding via Three-Tower Graph Convolutional Networks., , , and . ICDM, page 1035-1040. IEEE, (2022)MARIO: Modality-Aware Attention and Modality-Preserving Decoders for Multimedia Recommendation., , , and . CIKM, page 993-1002. ACM, (2022)Are Negative Links Really Beneficial to Network Embedding?: In-Depth Analysis and Interesting Results., , and . CIKM, page 2113-2116. ACM, (2020)ASiNE: Adversarial Signed Network Embedding., , , and . SIGIR, page 609-618. ACM, (2020)Recommendation of research papers in DBpia: A Hybrid approach exploiting content and collaborative data., , , , , , and . SMC, page 2966-2971. IEEE, (2016)Exploiting job transition patterns for effective job recommendation., , , and . SMC, page 2414-2419. IEEE, (2017)Linear, or Non-Linear, That is the Question!, , , , , , and . WSDM, page 517-525. ACM, (2022)