Automatically predicting shipper behavior using machine learning models
AssigneeUnited Parcel Service of America, Inc.
InventorsTed Abebe, Ed Hojecki, I. Lavrik, Vinay Rao, Donald Hickey
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Abstract
Embodiments are disclosed for autonomously predicting shipper behavior. An example method includes the following operations. One or more learning models are generated. Shipper behavior data for at least one shipper is extracted. The shipper behavior data includes a plurality of features associated with the at least one shipper scheduled to ship one or more parcels. It is predicted whether one or more shipments will be sent or arrive at a particular time based at least in part on running the plurality of features of the at least one shipper through the one or more learning models.
Claims20
An apparatus for autonomously predicting shipper behavior, the apparatus comprising:
- at least one non-transitory computer-readable storage medium that includes program instructions, the program instructions being executable by one or more processors to cause the one or more processors to:
- access one or more shipper information units from a shipper behavioral data management tool, wherein the one or more shipper information units comprise shipper behavioral data associated with one or more shippers, wherein the shipper behavioral data comprises one or more of:
- package received time, manifest package time, or package information;
- extract one or more features from the one or more shipper information units;
- and
- generate, via a shipper behavior learning model and the one or more features, an output comprising a shipper behavior prediction for the shipper.
A method for autonomously predicting shipper behavior, the method comprising:
- generating one or more learning models;
- extracting shipper behavior data for at least one shipper, the shipper behavior data includes a plurality of features associated with the at least one shipper scheduled to ship one or more parcels;
- and
- predicting whether one or more shipments will be sent or arrive at a particular time based at least in part on running the plurality of features of the at least one shipper through the one or more learning models.
A system comprising:
- at least one computing device having at least one processor;
- and
- at least one computer readable storage medium having program instructions embodied therewith, the program instructions readable/executable by the at least one processor to cause the system to:
- generate one or more learning models;
- extract shipper behavior data, the shipper behavior data includes a plurality of features of at least one package associated with one or more shipping operations of at least one shipper;
- and
- generate a prediction output corresponding to a size of the at least one package based at least in part on running the plurality of features of the at least one package through the one or more learning models.
Dependencies are inferred from the claim text.