Tackling cold-start with deep personalized transfer of user preferences for cross-domain recommendation
Author:
Publisher
Springer Science and Business Media LLC
Subject
Applied Mathematics,Computational Theory and Mathematics,Computer Science Applications,Modeling and Simulation,Information Systems
Link
https://link.springer.com/content/pdf/10.1007/s41060-023-00467-9.pdf
Reference38 articles.
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2. Ko, H., Lee, S., Park, Y., Choi, A.: A survey of recommendation systems: recommendation models, techniques, and application fields. Electronics 11(1), 141 (2022)
3. Sarwar, B., Karypis, G., Konstan, J., Riedl, J.: Item-based collaborative filtering recommendation algorithms. In: Proceedings of the 10th International Conference on World Wide Web, pp. 285–295 (2001)
4. Ko, H., Lee, S., Park, Y., Choi, A.: A survey of recommendation systems: recommendation models, techniques, and application fields. Electronics 11(1), 141 (2022)
5. Lee, D., Hosanagar, K.: Impact of recommender systems on sales volume and diversity (2014)
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