The University of Southampton
University of Southampton Institutional Repository

Breaking the habit: measuring and predicting departures from routine in individual human mobility

Breaking the habit: measuring and predicting departures from routine in individual human mobility
Breaking the habit: measuring and predicting departures from routine in individual human mobility
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
1574-1192
808-822
McInerney, J.
cf4e2deb-938c-45f2-98f4-cbeaaf5184f9
Stein, S.
cb2325e7-5e63-475e-8a69-9db2dfbdb00b
Rogers, A
f9130bc6-da32-474e-9fab-6c6cb8077fdc
Jennings, N. R.
ab3d94cc-247c-4545-9d1e-65873d6cdb30
McInerney, J.
cf4e2deb-938c-45f2-98f4-cbeaaf5184f9
Stein, S.
cb2325e7-5e63-475e-8a69-9db2dfbdb00b
Rogers, A
f9130bc6-da32-474e-9fab-6c6cb8077fdc
Jennings, N. R.
ab3d94cc-247c-4545-9d1e-65873d6cdb30

McInerney, J., Stein, S., Rogers, A and Jennings, N. R. (2013) Breaking the habit: measuring and predicting departures from routine in individual human mobility. Pervasive and Mobile Computing, 9 (6), 808-822. (doi:10.1016/j.pmcj.2013.07.016).

Record type: Article

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

Text
article.pdf - Other
Download (323kB)
Text
1-s2.0-S1574119213000989-main.pdf - Other
Download (901kB)

More information

e-pub ahead of print date: September 2013
Published date: 2013
Organisations: Agents, Interactions & Complexity

Identifiers

Local EPrints ID: 356175
URI: http://eprints.soton.ac.uk/id/eprint/356175
ISSN: 1574-1192
PURE UUID: c3c2807b-9a2c-46e6-bccc-43c87a6002f5
ORCID for S. Stein: ORCID iD orcid.org/0000-0003-2858-8857

Catalogue record

Date deposited: 02 Sep 2013 10:18
Last modified: 15 Mar 2024 03:30

Export record

Altmetrics

Contributors

Author: J. McInerney
Author: S. Stein ORCID iD
Author: A Rogers
Author: N. R. Jennings

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×