US 11,922,476 B2
Generating recommendations based on descriptors in a multi-dimensional search space
Kate Key, Powhatan, VA (US); Vincent Pham, Champaign, IL (US); Jeremy Goodsitt, Champaign, IL (US); Austin Walters, Savoy, IL (US); Galen Rafferty, Mahomet, IL (US); and Anh Truong, Champaign, IL (US)
Assigned to Capital One Services, LLC, McLean, VA (US)
Filed by Capital One Services, LLC, McLean, VA (US)
Filed on Jul. 1, 2021, as Appl. No. 17/365,272.
Prior Publication US 2023/0005038 A1, Jan. 5, 2023
Int. Cl. G06Q 30/00 (2023.01); G06Q 30/0601 (2023.01)
CPC G06Q 30/0625 (2013.01) 19 Claims
OG exemplary drawing
 
1. A computer implemented method for characterizing items using tuples in a multi-dimensional search space, the method comprising:
retrieving, from one or more databases, a training set comprising a plurality of known tuples each paired with associated parameters;
applying a machine learning algorithm to the training set to generate a classifier model;
storing the classifier model in the one or more databases;
acquiring, by a server via a computer network, transaction records from remote computing devices, wherein the transaction records identify purchases of the items;
extracting, from the transaction records, purchase parameters characterizing the purchases of the items, wherein the purchase parameters are variables of the classifier model;
generating, by the server using the classifier model and based on the purchase parameters, computed the tuples respectively representing the items in the multi-dimensional search space, wherein a measure of similarity between two of the items is indicated by a distance in the multi-dimensional search space between two of the computed tuples respectively representing the two of the items;
compiling item records, each including a different one of the computed tuples; and
storing the item records in one or more databases.