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A Novel Recommender System for helping Marathoners to Achieve a new Personal-Best
Author(s)
Date Issued
2017-08-31
Date Available
2017-11-28T12:47:55Z
Abstract
We describe a novel application for recommender systems -- helping marathon runners to run a new personal-best race-time -- by predicting a challenging, but achievable target-time, and by recommending a tailored race-plan to achieve this time. A comprehensive evaluation of prediction accuracy and race-plan quality is provided using a large-scale dataset with almost 400,000 runners from the last 12 years of the Chicago marathon.
Sponsorship
Science Foundation Ireland
Other Sponsorship
Insight Research Centre
Type of Material
Journal Article
Publisher
ACM
Start Page
116
End Page
120
Copyright (Published Version)
2017 ACM
Subjects
Language
English
Status of Item
Peer reviewed
Journal
RecSys '17 Proceedings of the Eleventh ACM Conference on Recommender Systems
Conference Details
RecSys '17 the Eleventh ACM Conference on Recommender Systems, Como, Italy, 27-31 August 2017
This item is made available under a Creative Commons License
File(s)
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Name
insight_publication.pdf
Size
299.14 KB
Format
Adobe PDF
Checksum (MD5)
a63875bad099a754cf930fd3cd089bad
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