Running Recommendations: Personalisation Opportunities for Health and Fitness

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Title: Running Recommendations: Personalisation Opportunities for Health and Fitness
Authors: Smyth, Barry
Permanent link: http://hdl.handle.net/10197/10124
Date: 11-Jul-2018
Online since: 2019-04-24T11:26:58Z
Abstract: The history of personalisation and recommender systems is, in large part, a web-tale: a story of sites and services that learn about users, in order to provide more tailored experiences. The rapid rise of mobile computing, combined with wearable sensors, and an increasingly connected IoT world, has begun to shift the potential for personalisation, from the virtual world of the web, to the physical world in which we live, work, and play. This talk will consider exciting new application opportunities for user modelling, personalisation, and recommendation in the area of personal health and fitness, with a particular emphasis on how these technologies can help people to exercise more effectively, and by drawing from recent results for marathon runners.
Type of material: Conference Publication
Publisher: ACM
Copyright (published version): 2018 the Author
Keywords: Recommender systemsSports analyticsData analytics
DOI: 10.1145/3209219.3209269
Other versions: http://www.um.org/umap2018/
Language: en
Status of Item: Peer reviewed
Is part of: UMAP '18 Proceedings of the 26th Conference on User Modeling, Adaptation and Personalization
Conference Details: The 26th Conference on User Modeling, Adaption and Personalization (UMAP'18), Nanyang Technological University, Singapore, 8-11 July 2018
ISBN: 978-1-4503-5589-6
Appears in Collections:Insight Research Collection

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