Title
Breaking the habit: Measuring and predicting departures from routine in individual human mobility
Abstract
Researchers studying daily life mobility patterns have recently shown that humans are typically highly predictable in their movements. However, no existing work has examined the boundaries of this predictability, where human behaviour transitions temporarily from routine patterns to highly unpredictable states. To address this shortcoming, we tackle two interrelated challenges. First, we develop a novel information-theoretic metric, called instantaneous entropy, to analyse an individual's mobility patterns and identify temporary departures from routine. Second, to predict such departures in the future, we propose the first Bayesian framework that explicitly models breaks from routine, showing that it outperforms current state-of-the-art predictors.
Year
DOI
Venue
2013
10.1016/j.pmcj.2013.07.016
Pervasive and Mobile Computing
Keywords
Field
DocType
current state-of-the-art predictor,mobility pattern,individual human mobility,bayesian framework,existing work,daily life mobility pattern,interrelated challenge,instantaneous entropy,human behaviour,models break,routine pattern,mobile computing,machine learning
Econometrics,Predictability,Computer science,Operations research,Context awareness,Mechanism design,Habit,Bayesian probability,Distributed computing
Journal
Volume
Issue
ISSN
9
6
1574-1192
Citations 
PageRank 
References 
24
0.84
23
Authors
4
Name
Order
Citations
PageRank
James McInerney122610.76
Sebastian Stein239442.61
alex rogers32500183.76
Nicholas R. Jennings4193481564.35