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A Game with a Purpose for Recommender Systems

Author(s)
Smyth, Barry  
Rafter, Rachael  
Banks, Sam  
Uri
http://hdl.handle.net/10197/9973
Date Issued
2015-11-11
Date Available
2019-04-16T09:13:46Z
Abstract
Recommender systems learn about our preferences to make targeted suggestions. In this paper we outline a novel game with-a-purpose designed to infer preferences at scale as aside-effect of gameplay. We evaluate the utility of this data in a recommendation context as part of a small live-user trial.
Sponsorship
Science Foundation Ireland
Type of Material
Conference Publication
Publisher
AAAI
Copyright (Published Version)
2015 Association for the Advancement of Artificial Intelligence
Subjects

Recommender Systems

Targeted suggestions

Web versions
https://www.humancomputation.com/2015/
Language
English
Status of Item
Peer reviewed
Journal
Gerber, E., Ipeirotis, P. (eds.). Proceedings of the Third AAAI Conference on Human Computation and Crowdsourcing (HCOMP 2015)
Conference Details
The Third AAAI Conference on Human Computation and Crowdsourcing (HCOMP 2015), San Diego, California, 8-11 November 2015
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
File(s)
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insight_publication.pdf

Size

1.33 MB

Format

Adobe PDF

Checksum (MD5)

f5fc250c2945e3a43b6d8e908dce946c

Owning collection
Insight Research Collection

Item descriptive metadata is released under a CC-0 (public domain) license: https://creativecommons.org/public-domain/cc0/.
All other content is subject to copyright.

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