Unearthing Undiscovered Interests: Knowledge Enhanced Representation Aggregation for Long-Tail Recommendation
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-46781-3_9
Reference12 articles.
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2. Zhang, Z., Kudo, Y., Murai, T., Ren, Y.: Improved covering-based collaborative filtering for new users’ personalized recommendations. Knowl. Inf. Syst. 62, 3133–3154 (2020). https://doi.org/10.1007/s10115-020-01455-2
3. Zhang, Z., Zhang, Y., Ren, Y.: Employing neighborhood reduction for alleviating sparsity and cold start problems in user-based collaborative filtering. Inf. Retrieval J. 23, 449–472 (2020). https://doi.org/10.1007/s10791-020-09378-w
4. Li, J., Lu, K., Huang, Z., Shen, H.T.: On both cold-start and long-tail recommendation with social data. IEEE Trans. Knowl. Data Eng. 33(1), 194–208 (2021). https://doi.org/10.1109/TKDE.2019.2924656
5. Zhang, Z., Dong, M., Ota, K., Kudo, Y.: Alleviating new user cold-start in user-based collaborative filtering via bipartite network. IEEE Trans. Comput. Soc. Syst. 7(3), 672–685 (2020). https://doi.org/10.1109/TCSS.2020.2971942
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