A Differential Privacy Framework for Collaborative Filtering
Focusing on the privacy issues in recommender systems, we propose a framework containing two perturbation methods for differentially private collaborative filtering to prevent the threat of inference attacks against users. To conceal individual ratings and provide valuable predictions, we consider s...
Main Authors: | , , , |
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Format: | Article |
Language: | English |
Published: |
Hindawi Limited
2019-01-01
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Series: | Mathematical Problems in Engineering |
Online Access: | http://dx.doi.org/10.1155/2019/1460234 |