Methods for predicting destinations from partial trajectories employing open-and closed-world modeling methods
The claimed subject matter provides systems and/or methods that facilitate inferring probability distributions over the destinations and/or routes of a user, from observations about context and partial trajectories of a trip. Destinations of a trip are based on at least one of a prior and a likeliho...
Saved in:
Main Authors | , |
---|---|
Format | Patent |
Language | English |
Published |
20.09.2011
|
Subjects | |
Online Access | Get full text |
Cover
Loading…
Summary: | The claimed subject matter provides systems and/or methods that facilitate inferring probability distributions over the destinations and/or routes of a user, from observations about context and partial trajectories of a trip. Destinations of a trip are based on at least one of a prior and a likelihood based at least in part on the received input data. The destination estimator component can use one or more of a personal destinations prior, time of day and day of week, a ground cover prior, driving efficiency associated with candidate locations, and a trip time likelihood to probabilistically predict the destination. In addition, data gathered from a population about the likelihood of visiting previously unvisited locations and the spatial configuration of such locations may be used to enhance the predictions of destinations and routes. |
---|---|
Bibliography: | Application Number: US20060426540 |