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Multi-task learning for collaborative filtering

Published:2021-11-13 Issue: Volume: Page:
ISSN:1868-8071
Container-title:International Journal of Machine Learning and Cybernetics
language:en
Short-container-title:Int. J. Mach. Learn. & Cyber.

Author:

Long Lianjie,Huang Faliang,Yin Yunfei,Xu Youquan

Funder

Natural Science Foundation of China

Guangxi Bagui Teams for Innovation and Research

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Software

Link

https://link.springer.com/content/pdf/10.1007/s13042-021-01451-0.pdf

Reference52 articles.

1. Ebesu T, Shen B, Fang Y (2018) Collaborative memory network for recommendation systems. In: The 41st International ACM SIGIR Conference on Research and Development in Information Retrieval, pp 515–524

2. Liang D, Krishnan RG, Hoffman MD, Jebara T (2018) Variational autoencoders for collaborative filtering. In: Proceedings of the 2018 World Wide Web Conference, pp 689–698

3. Sarwar B, Karypis G, Konstan J, Riedl J (2001) Item-based collaborative filtering recommendation algorithms. In: Proceedings of the 10th International Conference on World Wide Web, pp 285–295

4. Zhang H, Shen F, Liu W, He X, Luan H, Chua T-S (2016) Discrete collaborative filtering. In: Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval, pp 325–334

5. He X, Zhang H, Kan M-Y, Chua T-S (2016) Fast matrix factorization for online recommendation with implicit feedback. In: Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval, pp 549–558

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