A trustworthy model of recommender system using hyper-tuned restricted boltzmann machine
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Media Technology,Software
Link
https://link.springer.com/content/pdf/10.1007/s11042-021-11575-8.pdf
Reference21 articles.
1. Aalen OO, Johansen S (1978) An empirical transition matrix for non-homogeneous markov chains based on censored observations. Scand J Stat pp. 141–150
2. Abdollahi B, Nasraoui O (2016) Explainable restricted boltzmann machines for collaborative filtering. arXiv preprint arXiv:1606.07129
3. Amatriain X, Basilico J (2015) Recommender systems in industry: A netflix case study. In: Recommender systems handbook. Springer, pp 385–419
4. Ferreira D, Silva S, Abelha A, Machado J (2020) Recommendation system using autoencoders. Appl Sci 10(16):5510
5. Fischer A, Igel C (2012) An introduction to restricted boltzmann machines. In: Iberoamerican congress on pattern recognition. Springer, pp 14–36
Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. An improved restricted Boltzmann Machine using Bayesian Optimization for Recommender Systems;Evolving Systems;2023-09-27
2. AI-Enabled Trust in Distributed Networks;IEEE Access;2023
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