Knowledge Transfer for Cross-Domain Book Recommender System
Author:
Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-68675-7_27
Reference11 articles.
1. Ashish Kumar Sahu, P.D.: Knowledge transfer by domain-independent user latent factor for cross-domain recommender systems. In: Future Generation Computer Systems, pp. 320–333 (2020)
2. Zhang, Q., et al.: A cross-domain recommender system with consistent information transfer. Decis. Support Syst. 104, 49–63 (2017)
3. Bokde, D., Girase, S., Mukhopadhyay, D.: Matrix factorization model in collaborative filtering algorithms: a survey. Procedia Comput. Sci. 49, 136–146 (2015). https://doi.org/10.1016/j.procs.2015.04.237
4. Sahu, A.K., Dwivedi, P.: Aligned intrinsic user factors knowledge transfer for cross-domain recommender systems. Procedia Comput. Sci. 167, 363–372 (2020). https://doi.org/10.1016/j.procs.2020.03.237
5. Liu, T., Deng, X., He, Z., Long, Y.: TCD-CF: Triple cross-domain collaborative filtering recommendation. Pattern Recognit. Lett. 149, 185–192 (2021). https://doi.org/10.1016/j.patrec.2021.06.016
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