Editorial: Privacy-preserving recommender systems with formal guarantees
Daniel Bellini1*
1Department of History, Yangtze Normal University, China
* Corresponding author.
Trans. Intell. Comput. Syst. 2023, 1(2), e6930; https://doi.org/10.58304/9gdwv616
Introduction
Over the past decade, work on editorial: privacy-preserving recommender systems with formal guarantees has grown from a specialist concern into a field with its own methods, journals and communities. This editorial introduces the contributions in this issue and places them in a wider context.
Three themes run through the articles. First, the authors pay close attention to the quality of the underlying evidence and to the assumptions that connect it to the conclusions. Second, they take reproducibility seriously: data, code and protocols are shared wherever possible. Third, they are candid about the limits of their findings.
In this issue
We are grateful to the reviewers, who gave generously of their time, and to the members of the editorial board for their advice. We also thank the editorial office for its careful work on every manuscript.
The journal will continue to publish work that is rigorous, clearly written and openly available. We welcome suggestions from readers and invite submissions in all areas within our scope.
Declarations
Funding
The authors acknowledge support from the Wellcome Trust (grant 215801/Z/19/Z) and the National Institute for Health and Care Research.
Data Availability
All data supporting the findings are available in the supplementary material and in a public repository.
Copyright and License
© 2023 Aurora Computing Society