Abstract
It is important for recommender system designers and service providers to learn about ways to generate accurate recommendations while at the same time respecting the privacy of their users. In this tutorial, we analyze common privacy risks imposed by recommender systems, survey privacy-enhanced recommendation techniques, and discuss implications for users.
Original language | English |
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Title of host publication | Proceedings of the Eleventh ACM Conference on Recommender Systems |
Subtitle of host publication | RecSys '17 |
Place of Publication | New York |
Publisher | Association for Computing Machinery (ACM) |
Pages | 394-395 |
Number of pages | 2 |
ISBN (Electronic) | 9781450346528 |
DOIs | |
Publication status | Published - 2017 |
Externally published | Yes |
Event | 11th ACM Conference on Recommender Systems, RecSys '17 - Como, Italy Duration: 27 Aug 2017 → 31 Aug 2017 |
Conference
Conference | 11th ACM Conference on Recommender Systems, RecSys '17 |
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Country | Italy |
City | Como |
Period | 27/08/17 → 31/08/17 |
Keywords
- privacy
- recommender systems
- Privacy
- Recommender systems