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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.

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

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More information

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

Identifiers

Local EPrints ID: 356175
URI: https://eprints.soton.ac.uk/id/eprint/356175
ISSN: 1574-1192
PURE UUID: c3c2807b-9a2c-46e6-bccc-43c87a6002f5

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Date deposited: 02 Sep 2013 10:18
Last modified: 10 Nov 2017 06:30

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Contributors

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

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