Privacy for recommender systems

tutorial abstract

Bart P. Knijnenburg, Shlomo Berkovsky

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

7 Citations (Scopus)


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 languageEnglish
Title of host publicationProceedings of the Eleventh ACM Conference on Recommender Systems
Subtitle of host publicationRecSys '17
Place of PublicationNew York
PublisherAssociation for Computing Machinery (ACM)
Number of pages2
ISBN (Electronic)9781450346528
Publication statusPublished - 2017
Externally publishedYes
Event11th ACM Conference on Recommender Systems, RecSys '17 - Como, Italy
Duration: 27 Aug 201731 Aug 2017


Conference11th ACM Conference on Recommender Systems, RecSys '17


  • privacy
  • recommender systems
  • Privacy
  • Recommender systems

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