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A data-driven study on preferred situations for running

Open access

A data-driven study on preferred situations for running

Open access

Samenvatting

We analyzed a large data set from a mobile exercise application to find the preferred running situations of a large number of users. We categorized the users according to their running behaviors (i.e. regularly active, or rarely ac-tive over the year), then studied the influence of 15 features, including temporal, geographical and weather-based features for different user groups. We found that geographical features influence the behavior of less active runners.

OrganisatieHogeschool van Amsterdam
Gepubliceerd in2018 ACM International Joint Conference and 2018 International Symposium on Pervasive and Ubiquitous Computing and Wearable Computers Singapore, Singapore, SGP
Datum2018-10
TypeConferentiebijdrage
DOI10.1145/3267305.3267552
TaalEngels

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