Personalized Audiobook Recommendations at Spotify Through Graph Neural Networks-Reference-Cited by-同舟云学术

Personalized Audiobook Recommendations at Spotify Through Graph Neural Networks

Published:2024-05-13 Issue: Volume: Page:403-412
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Container-title:Companion Proceedings of the ACM Web Conference 2024
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Author:

De Nadai Marco¹^ORCID,Fabbri Francesco²^ORCID,Gigioli Paul³^ORCID,Wang Alice⁴^ORCID,Li Ang⁵^ORCID,Silvestri Fabrizio⁶^ORCID,Kim Laura³^ORCID,Lin Shawn⁴^ORCID,Radosavljevic Vladan³^ORCID,Ghael Sandeep³^ORCID,Nyhan David³^ORCID,Bouchard Hugues²^ORCID,Lalmas Mounia⁷^ORCID,Damianou Andreas⁸^ORCID

Affiliation:

1. Spotify, Copenhagen, Denmark

2. Spotify, Barcelona, Spain

3. Spotify, New York, USA

4. Spotify, New York, NY, USA

5. Spotify, Harrisburg, PA, USA

6. Spotify & Sapienza University of Rome, Rome, Italy

7. Spotify, London, United Kingdom

8. Spotify, Cambridge, United Kingdom

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3589335.3648339

Reference49 articles.

1. N. K. Ahmed, R. A. Rossi, R. Zhou, J. B. Lee, X. Kong, T. L. Willke, and H. Eldardiry. Inductive representation learning in large attributed graphs. arXiv preprint arXiv:1710.09471, 2017.

2. E. Bernhardsson. Annoy. https://github.com/spotify/annoy.

3. A. Bordes, N. Usunier, A. Garcia-Duran, J.Weston, and O. Yakhnenko. Translating embeddings for modeling multi-relational data. Advances in neural information processing systems, 26, 2013.

4. Graph Heterogeneous Multi-Relational Recommendation

5. A Comprehensive Survey of Knowledge Graph-Based Recommender Systems: Technologies, Development, and Contributions

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