DYNAMICALLY GENERATING AND UPDATING MULTIPLIERS FOR A TRANSPORTATION MATCHING SYSTEM USING MACHINE LEARNING

This disclosure covers machine-learning methods, non-transitory computer readable media, and systems that generate a multiplier that efficiently and effectively provides on-demand transportation services for a geographic area. The methods, non-transitory computer readable media, and systems dynamica...

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Bibliographische Detailangaben
Hauptverfasser: Sholley, Christopher, Frederick, Adriel, Chachra, Ricky, Thai, Jerome Hong-Phat, Chiao, Tzu-Hsin, Shekhawat, Ashivni
Format: Patent
Sprache:eng
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Beschreibung
Zusammenfassung:This disclosure covers machine-learning methods, non-transitory computer readable media, and systems that generate a multiplier that efficiently and effectively provides on-demand transportation services for a geographic area. The methods, non-transitory computer readable media, and systems dynamically adjust the multiplier with machine learners to maintain a target estimated time of arrival for a provider device to fulfill a request received from a requestor device. In some embodiments, the methods, non-transitory computer readable media, and systems generate a multiplier report comprising a representation of a geographic area and an indication of the multiplier to facilitate inflow and outflow of provider devices within and without the geographic area.