A User-Centered Location Model
Personal and Ubiquitous Computing
Using GPS to learn significant locations and predict movement across multiple users
Personal and Ubiquitous Computing
Learning and inferring transportation routines
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Predestination: inferring destinations from partial trajectories
UbiComp'06 Proceedings of the 8th international conference on Ubiquitous Computing
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Predictive models of destinations represent an opportunity in the context of the increasing availability and sophistication of in-car driving aids. We present analyses of drivers' destinations based on GPS data recorded from 180 volunteer subjects. We focus on the probability of observing drivers visit previously unobserved destinations given time of day and day of week, and the rate of decline of observing such new destinations with time. For the latter, we discover a statistically significant difference based on gender.