When Newer is Not Better: Does Deep Learning Really Benefit Recommendation From Implicit Feedback?-Reference-Cited by-同舟云学术

When Newer is Not Better: Does Deep Learning Really Benefit Recommendation From Implicit Feedback?

Published:2023-07-18 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval
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Author:

Dong Yushun¹^ORCID,Li Jundong¹^ORCID,Schnabel Tobias²^ORCID

Affiliation:

1. University of Virginia, Charlottesville, USA

2. Microsoft, Redmond, USA

Funder

National Science Foundation

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3539618.3591785

Reference96 articles.

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3. Vito Walter Anelli , Alejandro Bellog'in , Tommaso Di Noia , Dietmar Jannach, and Claudio Pomo. 2022 . Top-n recommendation algorithms: A quest for the state-of-the-art. arXiv preprint arXiv:2203.01155 (2022). Vito Walter Anelli, Alejandro Bellog'in, Tommaso Di Noia, Dietmar Jannach, and Claudio Pomo. 2022. Top-n recommendation algorithms: A quest for the state-of-the-art. arXiv preprint arXiv:2203.01155 (2022).

4. Reenvisioning the comparison between Neural Collaborative Filtering and Matrix Factorization

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