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Session-based recommendation systems suggest relevant items to users by modeling user behavior and preferences using short-term anonymous sessions.
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P. Ren, Z. Chen, J. Li, Z. Ren, J. Ma, and M. de Rijke, “Repeatnet: A repeat aware neural recommendation machine for session-based recommendation,” Proceedings of the AAAI Conference on Artificial Intelligence , vol. 33, no. 01, pp. 4806–4813, Jul. 2019. [Online]. Available: https://ojs.aaai.org/index.php/AAAI/article/view/4408
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M. Wang, P. Ren, L. Mei, Z. Chen, J. Ma, and M. de Rijke, “A collaborative session-based recommendation approach with parallel memory modules,” in Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval , ser. SIGIR’19. New York, NY, USA: Association for Computing Machinery, 2019, p. 345–354. [Online]. Available: https://doi.org/10.1145/3331184.3331210
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T. Chen and R. C.-W. Wong, “Handling information loss of graph neural networks for session-based recommendation,” in Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining , 2020, pp. 1172–1180
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