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Up close, but not too personal : Hypotargeting for recommender systems. / Larson, Martha; Slokom, Manel.

ImpactRS 2019 Impact of Recommender Systems 2019: Proceedings of the 1st Workshop on the Impact of Recommender Systems co-located with 13th ACM Conference on Recommender Systems (ACM RecSys 2019). ed. / Oren Sar Shalom; Dietmar Jannach; Ido Guy . CEUR-WS.org, 2019. p. 1-2 (CEUR Workshop Proceedings; Vol. 2462).

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

Harvard

Larson, M & Slokom, M 2019, Up close, but not too personal: Hypotargeting for recommender systems. in OS Shalom, D Jannach & I Guy (eds), ImpactRS 2019 Impact of Recommender Systems 2019: Proceedings of the 1st Workshop on the Impact of Recommender Systems co-located with 13th ACM Conference on Recommender Systems (ACM RecSys 2019). CEUR Workshop Proceedings, vol. 2462, CEUR-WS.org, pp. 1-2, 1st Workshop on the Impact of Recommender Systems, ImpactRS 2019, Copenhagen, Denmark, 19/09/19. <http://ceur-ws.org/Vol-2462/>

APA

Larson, M., & Slokom, M. (2019). Up close, but not too personal: Hypotargeting for recommender systems. In O. S. Shalom, D. Jannach, & I. Guy (Eds.), ImpactRS 2019 Impact of Recommender Systems 2019: Proceedings of the 1st Workshop on the Impact of Recommender Systems co-located with 13th ACM Conference on Recommender Systems (ACM RecSys 2019) (pp. 1-2). (CEUR Workshop Proceedings; Vol. 2462). CEUR-WS.org. http://ceur-ws.org/Vol-2462/

Vancouver

Larson M, Slokom M. Up close, but not too personal: Hypotargeting for recommender systems. In Shalom OS, Jannach D, Guy I, editors, ImpactRS 2019 Impact of Recommender Systems 2019: Proceedings of the 1st Workshop on the Impact of Recommender Systems co-located with 13th ACM Conference on Recommender Systems (ACM RecSys 2019). CEUR-WS.org. 2019. p. 1-2. (CEUR Workshop Proceedings).

Author

Larson, Martha ; Slokom, Manel. / Up close, but not too personal : Hypotargeting for recommender systems. ImpactRS 2019 Impact of Recommender Systems 2019: Proceedings of the 1st Workshop on the Impact of Recommender Systems co-located with 13th ACM Conference on Recommender Systems (ACM RecSys 2019). editor / Oren Sar Shalom ; Dietmar Jannach ; Ido Guy . CEUR-WS.org, 2019. pp. 1-2 (CEUR Workshop Proceedings).

BibTeX

@inproceedings{d6a9d899f8f0458aa90c6ef4080b4a31,
title = "Up close, but not too personal: Hypotargeting for recommender systems",
abstract = "Hypotargeting for recommender systems (hyporec) is the idea of controlling the number of unique lists of items that a recommender system can recommend to users during a given time period. The main advantage of hyporec is oversight. If a recommender system offers only a finite number of unique lists, then it becomes feasible for a person without technological knowledge to audit the recommender system. Oversight makes it possible to spot filter bubbles or cases in which users are being bombarded with divisive content. We argue that hyporec is actually not so far from many existing recommender system ideas, and that with further research hyporec systems could be capable of making good tradeoffs between the number of unique lists, rate of list renewal (which controls coverage), and conventional evaluation metrics for user satisfaction.",
keywords = "Oversight, Personalization, Position paper",
author = "Martha Larson and Manel Slokom",
year = "2019",
language = "English",
series = "CEUR Workshop Proceedings",
publisher = "CEUR-WS.org",
pages = "1--2",
editor = "Shalom, {Oren Sar} and Dietmar Jannach and {Guy }, {Ido }",
booktitle = "ImpactRS 2019 Impact of Recommender Systems 2019",
note = "1st Workshop on the Impact of Recommender Systems, ImpactRS 2019 ; Conference date: 19-09-2019 Through 19-09-2019",

}

RIS

TY - GEN

T1 - Up close, but not too personal

T2 - 1st Workshop on the Impact of Recommender Systems, ImpactRS 2019

AU - Larson, Martha

AU - Slokom, Manel

PY - 2019

Y1 - 2019

N2 - Hypotargeting for recommender systems (hyporec) is the idea of controlling the number of unique lists of items that a recommender system can recommend to users during a given time period. The main advantage of hyporec is oversight. If a recommender system offers only a finite number of unique lists, then it becomes feasible for a person without technological knowledge to audit the recommender system. Oversight makes it possible to spot filter bubbles or cases in which users are being bombarded with divisive content. We argue that hyporec is actually not so far from many existing recommender system ideas, and that with further research hyporec systems could be capable of making good tradeoffs between the number of unique lists, rate of list renewal (which controls coverage), and conventional evaluation metrics for user satisfaction.

AB - Hypotargeting for recommender systems (hyporec) is the idea of controlling the number of unique lists of items that a recommender system can recommend to users during a given time period. The main advantage of hyporec is oversight. If a recommender system offers only a finite number of unique lists, then it becomes feasible for a person without technological knowledge to audit the recommender system. Oversight makes it possible to spot filter bubbles or cases in which users are being bombarded with divisive content. We argue that hyporec is actually not so far from many existing recommender system ideas, and that with further research hyporec systems could be capable of making good tradeoffs between the number of unique lists, rate of list renewal (which controls coverage), and conventional evaluation metrics for user satisfaction.

KW - Oversight

KW - Personalization

KW - Position paper

UR - http://www.scopus.com/inward/record.url?scp=85073520232&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:85073520232

T3 - CEUR Workshop Proceedings

SP - 1

EP - 2

BT - ImpactRS 2019 Impact of Recommender Systems 2019

A2 - Shalom, Oren Sar

A2 - Jannach, Dietmar

A2 - Guy , Ido

PB - CEUR-WS.org

Y2 - 19 September 2019 through 19 September 2019

ER -

ID: 68753745