Quantification of human behavior is of prime interest in many applications ranging from behavioral science to practical applications like 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.
|Title of host publication||IEEE International Workshop on Machine Learning for Signal Processing|
|Publication status||Published - 2010|
|Event||2010 IEEE International Workshop on Machine Learning for Signal Processing - Kittilä, Finland|
Duration: 29 Aug 2010 → 1 Sep 2010
|Workshop||2010 IEEE International Workshop on Machine Learning for Signal Processing|
|Period||29/08/2010 → 01/09/2010|