Users’ Preference-Aware Music Recommendation with Contrastive Learning
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-97-5615-5_25
Reference24 articles.
1. Wang, D., Zhang, X., Yu, D., Xu, G., Deng, S.: Came: content-and context-aware music embedding for recommendation. IEEE Trans. Neural Networks Learn. Syst. 32(3), 1375–1388 (2020)
2. Sánchez-Moreno, D., González, A.B.G., Vicente, M.D.M., Batista, V.F.L., García, M.N.M.: A collaborative filtering method for music recommendation using playing coefficients for artists and users. Expert Syst. Appl. 66, 234–244 (2016)
3. Lee, W.P., Chen, C.T., Huang, J.Y., Liang, J.Y.: A smartphone-based activity-aware system for music streaming recommendation. Knowl.-Based Syst. 131, 70–82 (2017)
4. Wang, D., Deng, S., Xu, G.: Sequence-based context-aware music recommendation. Inf. Retrieval J. 21, 230–252 (2018)
5. Deldjoo, Y., Schedl, M., Knees, P.: Content-driven music recommendation: evolution, state of the art, and challenges. Comput. Sci. Rev. 51, 100618 (2024)
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