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2011
Springer

Enabling large-scale human activity inference on smartphones using community similarity networks (csn)

8 years 11 months ago
Enabling large-scale human activity inference on smartphones using community similarity networks (csn)
Sensor-enabled smartphones are opening a new frontier in the development of mobile sensing applications. The recognition of human activities and context from sensor-data using classification models underpins these emerging applications. However, conventional approaches to training classifiers struggle to cope with the diverse user populations routinely found in large-scale popular mobile applications. Differences between users (e.g., age, sex, behavioral patterns, lifestyle) confuse classifiers, which assume everyone is the same. To address this, we propose Community Similarity Networks (CSN), which incorporates inter-person similarity measurements into the classifier training process. Under CSN every user has a unique classifier that is tuned to their own characteristics. CSN exploits crowd-sourced sensordata to personalize classifiers with data contributed from other similar users. This process is guided by similarity networks that measure different dimensions of inter-person ...
Nicholas D. Lane, Ye Xu, Hong Lu, Shaohan Hu, Tanz
Added 23 Dec 2011
Updated 23 Dec 2011
Type Journal
Year 2011
Where HUC
Authors Nicholas D. Lane, Ye Xu, Hong Lu, Shaohan Hu, Tanzeem Choudhury, Andrew T. Campbell, Feng Zhao
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