Music Recommender System Based on Play Count Using Singular Value Decomposition++
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M. Schulz, S. Weinzierl, and J. Steffens, “The Impact of Choice Overload on Music Listening Experience,†2021.
A. Biswal, M. D. Borah, and Z. Hussain, “Music recommender system using restricted Boltzmann machine with implicit feedback,†in Advances in Computers, Academic Press Inc., 2021, pp. 367–402. doi: 10.1016/bs.adcom.2021.01.001.
Z. Romadhon, E. Sediyono, and C. E. Widodo, “Various Implementation of Collaborative Filtering-Based Approach on Recommendation Systems using Similarity,†Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control, pp. 179–186, Jul. 2020, doi: 10.22219/kinetik.v5i3.1062.
M. Jalili, S. Ahmadian, M. Izadi, P. Moradi, and M. Salehi, “Evaluating Collaborative Filtering Recommender Algorithms: A Survey,†IEEE Access, vol. 6, pp. 74003–74024, 2018, doi: 10.1109/ACCESS.2018.2883742.
A. M. A. Al-Sabaawi, H. Karacan, and Y. E. Yenice, “Svd++ and clustering approaches to alleviating the cold-start problem for recommendation systems,†International Journal of Innovative Computing, Information and Control, vol. 17, no. 2, pp. 383–396, 2021, doi: 10.24507/ijicic.17.02.383.
M. Srifi, A. Oussous, A. A. Lahcen, and S. Mouline, “Recommender systems based on collaborative filtering using review texts-A survey,†Information (Switzerland), vol. 11, no. 6. MDPI AG, Jun. 01, 2020. doi: 10.3390/INFO11060317.
D. Jannach, L. Lerche, and M. Zanker, “Recommending based on implicit feedback,†in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Springer Verlag, 2018, pp. 510–569. doi: 10.1007/978-3-319-90092-6_14.
Q. Zhao, F. M. Harper, G. Adomavicius, and J. A. Konstan, “Explicit or implicit feedback? engagement or satisfaction?: A field experiment on machine-learning-based recommender systems,†in Proceedings of the ACM Symposium on Applied Computing, Association for Computing Machinery, Apr. 2018, pp. 1331–1340. doi: 10.1145/3167132.3167275.
D. Bokde, S. Girase, and D. Mukhopadhyay, “Matrix Factorization model in Collaborative Filtering algorithms: A survey,†in Procedia Computer Science, Elsevier B.V., 2015, pp. 136–146. doi: 10.1016/j.procs.2015.04.237.
Rachana Mehta and Keyur Rana, “A review on matrix factorization techniques in recommender systems,†in Proc. 2nd Int. Conf. Commun. Syst. Comput. IT Appl. (CSCITA), 2017, pp. 269–274. doi: 10.1109/CSCITA.2017.8066567.
S. Jiang, J. Li, and W. Zhou, “AN APPLICATION OF SVD++ METHOD IN COLLABORATIVE FILTERING,†in 2020 17th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP), 2020, pp. 192–197. doi: 10.1109/ICCWAMTIP51612.2020.9317347/20/$31.00.
H. Tian, H. Cai, J. Wen, S. Li, and Y. Li, A Music Recommendation System Based on logistic regression and eXtreme Gradient Boosting. 2019. doi: 10.1109/IJCNN.2019.8852094.
T. Bertin-Mahieux, D. P. W. Ellis, B. Whitman, and P. Lamere, “The Million Song Dataset,†in Proceedings of the 12th International Conference on Music Information Retrieval (ISMIR), 2011. doi: 10.7916/D8377K1H.
Y. Dong, X. Guo, and Y. Gu, “Music Recommendation System based on Fusion Deep Learning Models,†in Journal of Physics: Conference Series, Institute of Physics Publishing, Jun. 2020. doi: 10.1088/1742-6596/1544/1/012029.
G. Liu and X. Zhao, “Recommender System for Books in University Library with Implicit Data,†in Proceedings of the 2018 International Conference on Network, Communication, Computer Engineering (NCCE), 2018, pp. 164–168. doi: 10.2991/ncce-18.2018.28.
A. Pujahari and D. S. Sisodia, “Model-Based Collaborative Filtering for Recommender Systems: An Empirical Survey,†in 2020 First International Conference on Power, Control and Computing Technologies (ICPC2T), 2020. doi: https://doi.org/10.1109/ICPC2T48082.2020.9071454.
S. H. Chen, S. I. Sou, and H. P. Hsieh, “HPCF: Hybrid Music Group Recommendation System based on Item Popularity and Collaborative Filtering,†in Proceedings - 2020 International Computer Symposium, ICS 2020, Institute of Electrical and Electronics Engineers Inc., Dec. 2020, pp. 43–49. doi: 10.1109/ICS51289.2020.00019.
J. Jiao, X. Zhang, F. Li, and Y. Wang, “A Novel Learning Rate Function and Its Application on the SVD++ Recommendation Algorithm,†IEEE Access, vol. 8, pp. 14112–14122, 2020, doi: 10.1109/ACCESS.2019.2960523.
N. Hug, “Surprise: A Python library for recommender systems,†Journal of Open Source Software, vol. 5, no. 52, p. 2174, Aug. 2020, doi: 10.21105/joss.02174.
F. Pedregosa et al., “Scikit-learn: Machine Learning in Python,†Journal of Machine Learning Research, vol. 12, pp. 2825–2830, 2011, doi: 10.48550/arXiv.1201.0490.
DOI: https://doi.org/10.30865/mib.v7i3.6424
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