ASCM: Analysis of a Sequential and Collaborative Model for Recommendations
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Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s42979-024-03168-7.pdf
Reference40 articles.
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2. Althbiti A, Alshamrani R, Alghamdi T, et al. Addressing data sparsity in collaborative filtering based recommender systems using clustering and artificial neural network. In: 2021 IEEE 11th Annual Computing and Communication Workshop and Conference (CCWC). IEEE; 2021. p. 0218–27.
3. Bokde D, Girase S, Mukhopadhyay D. Matrix factorization model in collaborative filtering algorithms: a survey. In: Procedia Computer Science. 2015. https://doi.org/10.1016/j.procs.2015.04.237.
4. Cheng HT, Koc L, Harmsen J, et al. Wide & deep learning for recommender systems. In: ACM International Conference Proceeding Series. 2016. https://doi.org/10.1145/2988450.2988454.
5. Duma M, Twala B. Optimising latent features using artificial immune system in collaborative filtering for recommender systems. Appl Soft Comput J. 2018. https://doi.org/10.1016/j.asoc.2018.07.001.
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