Data science for next-generation recommender systems-Reference-Cited by-同舟云学术

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Data science for next-generation recommender systems

Published:2023-06-29 Issue:2 Volume:16 Page:135-145
ISSN:2364-415X
Container-title:International Journal of Data Science and Analytics
language:en
Short-container-title:Int J Data Sci Anal

Author:

Wang Shoujin,Wang Yan,Sivrikaya Fikret,Albayrak Sahin,Anelli Vito Walter

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics,Computational Theory and Mathematics,Computer Science Applications,Modeling and Simulation,Information Systems

Link

https://link.springer.com/content/pdf/10.1007/s41060-023-00404-w.pdf

Reference83 articles.

1. Wang, S., Pasi, G., Hu, L., Cao, L.: The era of intelligent recommendation: editorial on intelligent recommendation with advanced ai and learning. IEEE Intell. Syst. 35(5), 3–6 (2020)

2. Wang, S., Zhang, X., Wang, Y., Liu, H., Ricci, F.: Trustworthy recommender systems. arXiv preprint http://arxiv.org/abs/2208.06265 (2022)

3. Wang, S., Liu, N., Zhang, X., Wang, Y., Ricci, F., Mobasher, B.: Data science and artificial intelligence for responsible recommendations. In: Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, pp. 4904–4905 (2022)

4. Goldberg, D., Nichols, D., Oki, B.M., Terry, D.: Using collaborative filtering to weave an information tapestry. Commun. ACM 35(12), 61–70 (1992)

5. Rong, X.: word2vec parameter learning explained. arXiv preprint http://arxiv.org/abs/1411.2738 (2014)

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