发明名称 |
PREDICTING AND UTILIZING VARIABILITY OF TRAVEL TIMES IN MAPPING SERVICES |
摘要 |
A system for predicting variability of travel time for a trip at a particular time may utilize a machine learning model including latent variables that are associated with the trip. The machine learning model may be trained from historical trip data that is based on location-based measurements reported from mobile devices. Once trained, the machine learning model may be utilized for predicting variability of travel time. A process may include receiving an origin, a destination, and a start time associated with a trip, obtaining candidate routes that run from the origin to the destination, and predicting, based at least in part on the machine learning model, a probability distribution of travel time for individual ones of the candidate routes. One or more routes may be recommended based on the predicted probability distribution, and a measure of travel time for the recommended route(s) may be provided. |
申请公布号 |
WO2016111857(A1) |
申请公布日期 |
2016.07.14 |
申请号 |
WO2015US67550 |
申请日期 |
2015.12.28 |
申请人 |
MICROSOFT TECHNOLOGY LICENSING, LLC |
发明人 |
WOODARD, DAWN;HORVITZ, ERIC, J.;NOGIN, GALINA;KOCH, PAUL, B.;RACZ, DAVID;GOLDSZMIDT, MOISES |
分类号 |
G06Q10/04 |
主分类号 |
G06Q10/04 |
代理机构 |
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代理人 |
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主权项 |
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地址 |
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