Up close, but not too personal

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

Larson, M.A. (TU Delft Multimedia Computing; Radboud Universiteit Nijmegen)
Slokom, M. (TU Delft Multimedia Computing)

Shalom, Oren Sar (editor)
Jannach, Dietmar (editor)
Guy, Ido (editor)

2019

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.

Oversight
Personalization
Position paper

http://resolver.tudelft.nl/uuid:d6a9d899-f8f0-458a-a90c-6ef4080b4a31

CEUR-WS.org

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)

1st Workshop on the Impact of Recommender Systems, ImpactRS 2019, 2019-09-19, Copenhagen, Denmark

CEUR Workshop Proceedings, 1613-0073, 2462

Institutional Repository

conference paper

© 2019 M.A. Larson, M. Slokom