Estimating Human Predictability From Mobile Sensor Data |
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| Abstract | Quantification of human behavior is of prime interest in many applications ranging from behavioral science to practical applications such as GSM resource planning and context-aware services. As proxies for humans, we apply multiple mobile phone sensors all conveying information about human behavior. Using a recent, information theoretic approach it is demonstrated that the trajectories of individual sensors are highly predictable given complete knowledge of the infinite past. We suggest using a new approach to time scale selection which demonstrates that participants have even higher predictability of non-trivial behavior on smaller timer scale than previously considered. |
| Type | Conference paper [With referee] |
| Conference | IEEE International Workshop on Machine Learning for Signal Processing |
| Year | 2010 Month August |
| BibTeX data | [bibtex] |
| IMM Group(s) | Intelligent Signal Processing |