Enhanced Privacy Preservation for Recommender Systems

Author:

Wu Ziqing1ORCID

Affiliation:

1. School of Computer Science and Engineering, NTU, Singapore

Publisher

ACM

Reference37 articles.

1. Willingness to share data: Contextual determinants of consumers' decisions to share private data with companies

2. Collaborative filtering with privacy

3. Aldo Gael Carranza , Rezsa Farahani , Natalia Ponomareva , Alex Kurakin , Matthew Jagielski , and Milad Nasr . 2023. Privacy-Preserving Recommender Systems with Synthetic Query Generation using Differentially Private Large Language Models. CoRR abs/2305.05973 ( 2023 ). https://doi.org/10.48550/arXiv.2305.05973 arXiv:2305.05973 10.48550/arXiv.2305.05973 Aldo Gael Carranza, Rezsa Farahani, Natalia Ponomareva, Alex Kurakin, Matthew Jagielski, and Milad Nasr. 2023. Privacy-Preserving Recommender Systems with Synthetic Query Generation using Differentially Private Large Language Models. CoRR abs/2305.05973 (2023). https://doi.org/10.48550/arXiv.2305.05973 arXiv:2305.05973

4. Controllable Multi-Interest Framework for Recommendation

5. Privacy Preserving Point-of-Interest Recommendation Using Decentralized Matrix Factorization

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