Mining User Interest Using Bayesian-PMF and Markov Chain Monte Carlo for Personalised Recommendation Systems
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-0550-8_9
Reference24 articles.
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3. L. Cheng, X. Tong, S. Wang, Y.C. Wu, H.V. Poor, Learning nonnegative factors from tensor data: probabilistic modeling and inference algorithm. IEEE Trans. Signal Process. 68, 1792–1806 (2020)
4. F. Ortega, R. Lara-Cabrera, Á. González-Prieto, J. Bobadilla, Providing reliability in recommender systems through Bernoulli matrix factorization. Inf. Sci. 553, 110–128 (2021)
5. X. Bui, H. Vu, O. Nguyen, K. Than, MAP estimation with Bernoulli randomness, and its application to text analysis and recommender systems. IEEE Access 8, 127818–127833 (2020)
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