Managing Cold-Start Issues in Music Recommendation Systems: An Approach Based on User Experience

Author:

Assunção Willian Garcias1ORCID,Prates Raquel Oliveira2ORCID,Zaina Luciana Aparecida Martinez3ORCID

Affiliation:

1. Department of Computer Science, Federal University of Sao Carlos, Brazil

2. Federal University of Minas Gerais, Brazil

3. Federal University of São Carlos, Brazil

Funder

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Conselho Nacional de Desenvolvimento Científico e Tecnológico

Publisher

ACM

Reference26 articles.

1. W.  G Assuncao and V.P.A Neris. 2018. An algorithm for music recommendation based on the user’s musical preferences and desired emotions . In Proceedings of the 17th International Conference on Mobile and Ubiquitous Multimedia. 205–213 . W. G Assuncao and V.P.A Neris. 2018. An algorithm for music recommendation based on the user’s musical preferences and desired emotions. In Proceedings of the 17th International Conference on Mobile and Ubiquitous Multimedia. 205–213.

2. Considering emotions and contextual factors in music recommendation

3. Jia-Wei Chang , Ching-Yi Chiou , Jia-Yi Liao , Ying-Kai Hung , Chien-Che Huang , Kuan-Cheng Lin , and Ying-Hung Pu. 2019. Music recommender using deep embedding-based features and behavior-based reinforcement learning. Multimedia Tools and Applications ( 2019 ), 1–28. Jia-Wei Chang, Ching-Yi Chiou, Jia-Yi Liao, Ying-Kai Hung, Chien-Che Huang, Kuan-Cheng Lin, and Ying-Hung Pu. 2019. Music recommender using deep embedding-based features and behavior-based reinforcement learning. Multimedia Tools and Applications (2019), 1–28.

4. Recsys challenge 2018

5. Intermediated Semiotic Inspection Method

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2. Beyond the Trends: Evolution and Future Directions in Music Recommender Systems Research;IEEE Access;2024

3. From User Context to Tailored Playlists: A User Centered Approach to Improve Music Recommendation System;Proceedings of the XXII Brazilian Symposium on Human Factors in Computing Systems;2023-10-16

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