@CONFERENCE\{IMM2010-05890,
    author       = "B. S. Jensen and J. E. Larsen and K. Jensen and J. Larsen and L. K. Hansen",
    title        = "Estimating Human Predictability From Mobile Sensor Data",
    year         = "2010",
    month        = "aug",
    booktitle    = "{IEEE} International Workshop on Machine Learning for Signal Processing",
    volume       = "",
    series       = "",
    editor       = "",
    publisher    = "",
    organization = "",
    address      = "",
    url          = "http://www2.compute.dtu.dk/pubdb/pubs/5890-full.html",
    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."
}