A Novel Recommender System for helping Marathoners to Achieve a new Personal-Best

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Title: A Novel Recommender System for helping Marathoners to Achieve a new Personal-Best
Authors: Smyth, BarryCunningham, Pádraig
Permanent link: http://hdl.handle.net/10197/9053
Date: 31-Aug-2017
Online since: 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.
Funding Details: Science Foundation Ireland
Funding Details: Insight Research Centre
Type of material: Journal Article
Publisher: ACM
Start page: 116
End page: 120
Copyright (published version): 2017 ACM
Keywords: Recommender Systems
DOI: 10.1145/3109859.3109874
Language: en
Status of Item: Peer reviewed
Is part of: 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: https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
Appears in Collections:Insight Research Collection

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