Federated Collaborative Filtering Recommendation Based on Semi-Homomorphic Encryption-Reference-Cited by-同舟云学术

Federated Collaborative Filtering Recommendation Based on Semi-Homomorphic Encryption

Published:2023-04-26 Issue: Volume: Page:
ISSN:
Container-title:2023 8th International Conference on Cloud Computing and Big Data Analytics (ICCCBDA)
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Author:

Niu Xiaohan¹,Zhang Xing¹,Chu Zhiguang²,Li Xiang¹

Affiliation:

1. Liaoning University of Technology,School of Electronics and Information Engineering, Key Laboratory of Security for Network and Data in Industrial Internet of Liaoning Province,Jinzhou,China

2. Beijing University of Technology,Faculty of Information Technology, Key Laboratory of Security for Network and Data in Industrial Internet of Liaoning Province,Jinzhou,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10154619/10154582/10154763.pdf?arnumber=10154763

Reference21 articles.

1. Matrix Factorization Techniques for Recommender Systems

2. Efficient neural matrix factorization without sampling for recommendation[J];chen;ACM Transactions on Information Systems (TOIS),2020

3. Large-Scale Parallel Collaborative Filtering for the Netflix Prize

4. Adaptive Bayesian personalized ranking for heterogeneous implicit feedbacks

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