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  5. Recommender Systems: A Healthy Obsession
 
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Recommender Systems: A Healthy Obsession

Author(s)
Smyth, Barry  
Uri
http://hdl.handle.net/10197/10916
Date Issued
2019-07-23
Date Available
2019-07-15T14:02:05Z
Abstract
We propose endurance sports as a rich and novel domain for recommender systems and machine learning research. As sports like marathon running, triathlons, and mountain biking become more and more popular among recreational athletes, there exists a growing opportunity to develop solutions to a number of interesting prediction, classification, and recommendation challenges, to better support the complex training and competition needs of athletes. Such solutions have the potential to improve the health and well-being of large populations of users, by promoting and optimising exercise as part of a productive and healthy lifestyle.
Sponsorship
Science Foundation Ireland
Other Sponsorship
Insight Research Centre
Type of Material
Journal Article
Publisher
AAAI Press
Journal
Proceedings of the AAAI Conference on Artificial Intelligence
Volume
33
Issue
1
Copyright (Published Version)
2019 Association for the Advancement of Artificial Intelligence
Subjects

Recommender systems

Collaborative filteri...

Content-based recomme...

Exercise

Machine learning

Web versions
https://aaai.org/Conferences/AAAI-19/aaai-19-senior-member-presentation-track/
Language
English
Status of Item
Peer reviewed
Conference Details
AAAI-19: 33rd AAAI Conference on Artificial Intelligence, Hilton Hawaiian Village, Honolulu, Hawaii, USA, 27 January - 1 February 2019
ISSN
2159-5399
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
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insight_publication.pdf

Size

104.62 KB

Format

Adobe PDF

Checksum (MD5)

3a7c85ef07d250894feaaed549fe70fa

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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