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Research Article
Music Recommendation System Using K-Nearest Neighbor Algorithm
Vijayalakshmi. P.R1
Divya Bharathi. P2
Jeyakarthika. C. S3
Haripriya.K4
1Professor, Department of Computer Science and Engineering, K.L.N. College of Engineering, Sivagangai, Tamilnadu, India. 2Assistant Professor, Department of Computer Science and Engineering, K.L.N. College of Engineering, Sivagangai, Tamilnadu, India. 3,4Student, Department of Computer Science and Engineering, K.L.N. College of Engineering, Sivagangai, Tamilnadu, India.
Published Online: September-October 2024
Pages: 43-45
Cite this article
No DOIReferences
[1]. Talal Liuchang Xu, Yezheng, Dayu Xu, and Liang Xu (2021) “Predicting the Preference for Sad Music: The Role of Gender,
Personality, and Audio Features” in IEEE Access, vol 9, pp. 152612-152623, doi: 10.1109/ACCESS.2021.3090940.
[2]. H. Tian, H. Cai, J. Wen, S. Li and Y. Li (2019), "A Music Recommendation System Based on logistic regression and eXtreme Gradient
Boosting," in International Joint Conference on Neural Networks (IJCNN), Budapest, Hungary, pp. 1-6, doi:
10.1109/IJCNN.2019.8852094.
[3]. M. R. Dalida, L. Bianca Aquino, W. C. Hod, R. Ann Agapor, S. L. Huyo-a and G. Avelino Sampedro (2022), "Music Mood Prediction
Based on Spotify’s Audio Features Using Logistic Regression," IEEE 14th International Conference on Humanoid, Nanotechnology,
Information Technology, Communication and Control, Environment, and Management (HNICEM), Boracay Island, Philippines, pp.
1-5, doi: 10.1109/HNICEM57413.2022.10109396.
[4]. V.Moscato, A.Picariello and G.Sperlí (2021), "An Emotional Recommender System for Music," in IEEE Intelligent Systems, vol. 36,
no. 5, pp. 57-68, doi: 10.1109/MIS.2020.3026000.
[5]. H. Park, S. Kim (2017), "A Hybrid Music Recommendation System Using Content-based Filtering and Collaborative Filtering," in
International Conference on Information and Communication Technology Convergence (ICTC),Jeju, South Korea, pp. 351-353, doi:
10.1109/ICTC.2017.8190980.
Personality, and Audio Features” in IEEE Access, vol 9, pp. 152612-152623, doi: 10.1109/ACCESS.2021.3090940.
[2]. H. Tian, H. Cai, J. Wen, S. Li and Y. Li (2019), "A Music Recommendation System Based on logistic regression and eXtreme Gradient
Boosting," in International Joint Conference on Neural Networks (IJCNN), Budapest, Hungary, pp. 1-6, doi:
10.1109/IJCNN.2019.8852094.
[3]. M. R. Dalida, L. Bianca Aquino, W. C. Hod, R. Ann Agapor, S. L. Huyo-a and G. Avelino Sampedro (2022), "Music Mood Prediction
Based on Spotify’s Audio Features Using Logistic Regression," IEEE 14th International Conference on Humanoid, Nanotechnology,
Information Technology, Communication and Control, Environment, and Management (HNICEM), Boracay Island, Philippines, pp.
1-5, doi: 10.1109/HNICEM57413.2022.10109396.
[4]. V.Moscato, A.Picariello and G.Sperlí (2021), "An Emotional Recommender System for Music," in IEEE Intelligent Systems, vol. 36,
no. 5, pp. 57-68, doi: 10.1109/MIS.2020.3026000.
[5]. H. Park, S. Kim (2017), "A Hybrid Music Recommendation System Using Content-based Filtering and Collaborative Filtering," in
International Conference on Information and Communication Technology Convergence (ICTC),Jeju, South Korea, pp. 351-353, doi:
10.1109/ICTC.2017.8190980.
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