Privacy for recommender systems: tutorial abstract

Bart P. Knijnenburg, Shlomo Berkovsky

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

8 Citations (Scopus)

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 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)
Pages394-395
Number of pages2
ISBN (Electronic)9781450346528
DOIs
Publication statusPublished - 2017
Externally publishedYes
Event11th ACM Conference on Recommender Systems, RecSys '17 - Como, Italy
Duration: 27 Aug 201731 Aug 2017

Conference

Conference11th ACM Conference on Recommender Systems, RecSys '17
CountryItaly
CityComo
Period27/08/1731/08/17

Keywords

  • privacy
  • recommender systems
  • Privacy
  • Recommender systems

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