Privacy for recommender systems: tutorial abstract

Bart P. Knijnenburg; Shlomo Berkovsky

doi:10.1145/3109859.3109935

Privacy for recommender systems: tutorial abstract

Bart P. Knijnenburg, Shlomo Berkovsky

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-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 language	English
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	https://doi.org/10.1145/3109859.3109935
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
Country	Italy
City	Como
Period	27/08/17 → 31/08/17

Keywords

privacy
recommender systems
Privacy
Recommender systems

Access to Document

10.1145/3109859.3109935

Link to publication in Scopus

Cite this

@inproceedings{4727454fad594bc3b033402e164a76ae,

title = "Privacy for recommender systems: tutorial abstract",

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.",

keywords = "privacy, recommender systems, Privacy, Recommender systems",

author = "Knijnenburg, {Bart P.} and Shlomo Berkovsky",

year = "2017",

doi = "10.1145/3109859.3109935",

language = "English",

pages = "394--395",

booktitle = "Proceedings of the Eleventh ACM Conference on Recommender Systems",

publisher = "Association for Computing Machinery (ACM)",

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note = "11th ACM Conference on Recommender Systems, RecSys '17 ; Conference date: 27-08-2017 Through 31-08-2017",

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AU - Berkovsky, Shlomo

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AB - 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.

KW - privacy

KW - recommender systems

KW - Privacy

KW - Recommender systems

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U2 - 10.1145/3109859.3109935

DO - 10.1145/3109859.3109935

M3 - Conference proceeding contribution

SP - 394

EP - 395

BT - Proceedings of the Eleventh ACM Conference on Recommender Systems

PB - Association for Computing Machinery (ACM)

CY - New York

Y2 - 27 August 2017 through 31 August 2017

ER -

Privacy for recommender systems: tutorial abstract

Abstract

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Keywords

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