Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/97092
Title: Predictability of individuals' mobility with high-resolution positioning data
Authors: Lin, Miao
Hsu, Wen-Jing
Lee, Zhuo Qi
Keywords: DRNTU::Engineering::Computer science and engineering
Issue Date: 2012
Source: Lin, M., Hsu, W.-J., & Lee, Z. Q. (2012). Predictability of individuals' mobility with high-resolution positioning data. Proceedings of the 2012 ACM Conference on Ubiquitous Computing - UbiComp '12, 381-390.
Abstract: The ability to foresee the next moves of a user is crucial to ubiquitous computing. Disregarding major differences in individuals' routines, recent ground-breaking analysis on mobile phone data suggests high predictability in mobility. By nature, however, mobile phone data offer very low spatial and temporal resolutions. It remains largely unknown how the predictability changes with respect to different spatial/temporal scales. Using high-resolution GPS data, this paper investigates the scaling effects on predictability. Given specified spatial-temporal scales, recorded trajectories are encoded into long strings of distinct locations, and several information-theoretic measures of predictability are derived. Somewhat surprisingly, high predictability is still present at very high spatial/temporal resolutions. Moreover, the predictability is independent of the overall mobility area covered. This suggests highly regular mobility behaviors. Moreover, by varying the scales over a wide range, an invariance is observed which suggests that certain trade-offs between the predicting accuracy and spatial-temporal resolution are unavoidable. As many applications in ubiquitous computing concern mobility, these findings should have direct implications.
URI: https://hdl.handle.net/10356/97092
http://hdl.handle.net/10220/11772
DOI: http://dx.doi.org/10.1145/2370216.2370274
Rights: © 2012 ACM.
metadata.item.grantfulltext: none
metadata.item.fulltext: No Fulltext
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