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Up close, but not too personal: Hypotargeting for recommender systems

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

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.
Original languageEnglish
Title of host publicationImpactRS 2019 - Proceedings of the 1st Workshop on the Impact of Recommender Systems, co-located with 13th ACM Conference on Recommender Systems, ACM RecSys 2019
EditorsO. Sar Shalom, D. Jannach, I. Guy
PublisherCEUR Workshop Proceedings
Volume2462
Publication statusPublished - 2019
Externally publishedYes
Event1st Workshop on the Impact of Recommender Systems, ImpactRS 2019 - Copenhagen, Denmark
Duration: 19 Sept 2019 → …

Publication series

NameCEUR Workshop Proceedings
ISSN (Print)1613-0073

Conference

Conference1st Workshop on the Impact of Recommender Systems, ImpactRS 2019
Country/TerritoryDenmark
CityCopenhagen
Period19/09/19 → …

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