Open Access
MATEC Web Conf.
Volume 309, 2020
2019 International Conference on Computer Science Communication and Network Security (CSCNS2019)
Article Number 03009
Number of page(s) 9
Section Smart Algorithms and Recognition
Published online 04 March 2020
  1. Salakhutdinov R, Mnih A. Bayesian probabilistic matrix factorization using markov chain monte carlo[C]//International Conference on Machine Learning. ACM, 2008. [Google Scholar]
  2. Yin J, Wang ZS, Li Q, Su WJ. Personalized recommendation based on large-scale implicit feedback. Ruan Jian Xue Bao/Journal of Software, 2014,25(9):1953–1966(in Chinese). [Google Scholar]
  3. Yu Chunhua, Liu Xuejun, Li Bin, et al. Context-aware recommendation of social information fusion in implicit feedback scenarios[J]. Computer Science, 2016, 43(6): 248–253. [Google Scholar]
  4. Yu Shuai, Lin Xuanxiong, Qiu Yuanyuan. A Word Vector Music Recommendation Model for Large-Scale Implicit Feedback. Computer Systems Applications, 2017, 26(11):28–35. [Google Scholar]
  5. Wang Zhisheng, Li Qi, Wang Jing, et al. Real-time personalized recommendation based on implicit user feedback data stream [J]. Chinese Journal of Computers, 2016(1): 52–64. [Google Scholar]
  6. He Ming, Sun Wang, Xiao Run, et al. A Collaborative Filtering Recommendation Algorithm Based on Fusion Clustering and User Interest Preference [J]. Computer Science, 2017(S2): 401–406. [Google Scholar]
  7. Li Tao, Fu Ding. Automated Implicit Grading Music Dual Recommendation System Based on Collaborative Filtering Algorithm [J]. Journal of Computer Measurement and Control, 2018, 26(11): 177–181. [Google Scholar]

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