Advanced Privacy-Preserving Federated Relationship Recommendation-Reference-Cited by-同舟云学术

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Advanced Privacy-Preserving Federated Relationship Recommendation

Published:2023-11-28 Issue: Volume:5 Page:248-252
ISSN:
Container-title:2023 5th International Conference on Artificial Intelligence and Computer Applications (ICAICA)
language:
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Author:

Xue Bin¹,Zheng Qinghua²,Zhao Weihu¹,Li Zhinan³,Cui Tianrun⁴,Feng Xue⁴

Affiliation:

1. School of Information and Communications, National University of Defense Technology,Wuhan,China

2. Xi'an Jiaotong University,Department of Computer Science and Technology,Xi'an,China

3. University Office, National University of Defense,Changsha,China

4. Tsinghua University,Laboratory of Flexible Electronics Technology,Beijing,China

Funder

National Natural Science Foundation of China

National University of Defense Technology

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10405420/10405394/10405503.pdf?arnumber=10405503

Reference16 articles.

1. Federated Collaborative Filtering Recommendation Based on Semi-Homomorphic Encryption

2. Cross-Domain Recommendation via User-Clustering and Multi-dimensional Information Fusion

3. Decentralized Gradient-Quantization Based Matrix Factorization for Fast Privacy-Preserving Point-of-Interest Recommendation

4. Federated collaborative filtering for privacy-preserving personalized recommendation system;Ammad-ud-din;arXiv preprint,2019

5. FedRec: Federated Recommendation With Explicit Feedback

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