A Data-driven Study on Preferred Situations for Running
| Authors |
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|---|---|
| Publication date | 2018 |
| Book title | UbiComp/ISWC '18 adjunct |
| Book subtitle | proceedings of the 2018 ACM International Joint Conference on Pervasive and Ubiquitous Computing and proceedings of the 2018 ACM International Symposium on Wearable Computers : October 8-12, 2018, Singapore, Singapore |
| ISBN (electronic) |
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| Event | 2018 ACM International Joint Conference on Pervasive and Ubiquitous Computing and 2018 ACM International Symposium on Wearable Computers |
| Pages (from-to) | 283-286 |
| Publisher | New York, NY: The Association for Computing Machinery |
| Organisations |
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| Abstract | 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 active 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. |
| Document type | Conference contribution |
| Note | Poster. |
| Language | English |
| Published at | https://doi.org/10.1145/3267305.3267552 |
| Downloads |
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