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US 12,591,921 B2Granted
Optimize shopping route using purchase embeddings
AssigneeCapital One Services, LLC
InventorsKate Key, Anh Truong, Jeremy Goodsitt, Galen Rafferty, Austin Walters, Vincent Pham
Life of this patent
Estimating the term…
Abstract
Aspects described herein may relate to methods, systems, and apparatuses that provide new capabilities for recommending purchases to a user based on the user's past purchasing history and the purchase history of others. A new descriptor referred to as “purchase embeddings” is disclosed, which are data records in a new multi-dimensional space for describing and tracking purchases of goods and services.
Claims20
A method, comprising:
- receiving purchase information relating to a first plurality of items, wherein the purchase information comprises data records in a multi-dimensional space;
- generating, using a classifier model, purchase embeddings from the data records in the multi-dimensional space;
- identifying, based on the purchase information, a correlation between purchases of the first plurality of items associated with a first geographic region;
- detecting a second geographic region;
- identifying a second plurality of items;
- calculating one or more measures of similarity between the first and the second pluralities of items;
- identifying, using a machine learning model and based on the purchase embeddings and the calculating, a subset of the second plurality of items that are available for purchase within the second geographic region with and the one or more measures of similarity to the first plurality of items;
- generating, based on the purchase embeddings and using the machine learning model, a proposed pattern for purchasing the subset within the second geographic region, wherein the proposed pattern provides one or more vendor locations within the second geographic region at which the subset is sold;
- sending instructions comprising the proposed pattern;
- receiving purchase information relating to the proposed pattern;
- and
- updating the machine learning model based on the received purchase information and the generated proposed pattern.
9 more elements
An apparatus, comprising:
- at least one computer processor;
- and
- computer memory comprising computer-executable instructions that when executed by the at least one computer processor, cause the apparatus to:
- receive purchase information relating to a first plurality of items, wherein the purchase information comprises data records in a multi-dimensional space;
- generate, using a classifier model, purchase embeddings from the data records in the multi-dimensional space;
- identify, based on the purchase information, a correlation between purchases of the first plurality of items associated with a first geographic region;
- detect a second geographic region;
- identify a second plurality of items;
- calculate one or more measures of similarity between the first and the second pluralities of items;
- identify, using a machine learning model and based on the purchase embeddings and the calculating, a subset of the second plurality of items that are available for purchase within the second geographic region with and the one or more measures of similarity to the first plurality of items;
- generate, based on the purchase embeddings and using the machine learning model, a proposed pattern for purchasing the subset within the second geographic region, wherein the proposed pattern provides one or more vendor locations within the second geographic region at which the subset is sold;
- send instructions comprising the proposed pattern;
- receive purchase information relating to the proposed pattern;
- and
- update the machine learning model based on the received purchase information and the generated proposed pattern.
12 more elements
A method, comprising:
- receiving purchase information, from a device, of a first plurality of items;
- generating, using a classifier model, purchase embeddings corresponding to multi-dimensional data records for the first plurality of items;
- identifying a correlation between the purchases of the first plurality of items;
- identifying a second geographic region that includes a location of the device;
- determining a second plurality of items;
- calculating one or more measures of similarity between the first and the second pluralities of items;
- identifying, using a machine learning model and based on the purchase embeddings, a subset of the second plurality of items within the second geographic region;
- generating, based on the subset and the purchase embeddings, and using the machine learning model, a proposed pattern for purchasing the subset within the second geographic region;
- sending, to the device, instructions with the proposed pattern for purchasing the subset;
- receiving purchase information relating to the proposed pattern for purchasing the subset;
- and
- updating the machine learning model based on the received purchase information and the generated proposed pattern.
9 more elements
Dependencies are inferred from the claim text.