US 11,694,121 B2Granted

Method for and system for predicting alimentary element ordering based on biological extraction

AssigneeKpn Innovations, LLC.

InventorKenneth Neumann

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Abstract

A system for predicting alimentary element ordering based on biological extraction, the system comprising a computing device configured to receive a biological extraction and alimentary element order chronicle of a user, retrieve an alimentary profile, identify, using the alimentary profile and a predictive machine-learning process, a predicted alimentary element and an alternative alimentary element, determine, using the predictive machine-learning process and the alimentary profile, the predicted alimentary element, select, using the predicted alimentary element, the alternative alimentary element, create a classifier, using a classification machine-learning process as a function of a plurality of alimentary element metrics, generate a plurality of related alimentary elements as a function of the classifier, rank the related alimentary elements as a function of the biological extraction, select the alternative alimentary element as a function of the ranking, and present the predicted alimentary element and the alternative alimentary element via a graphical user interface.

Claims20

Dependent claims

A system for predicting alimentary element ordering based on biological extraction, the system comprising:

a computing device, wherein the computing device is configured to:
receive a biological extraction of a user;
receive an alimentary element order chronicle of a user from a user device;
generating an alimentary profile, wherein retrieving the alimentary profile comprises:
training an alimentary machine-learning model with first training data that includes a plurality of entries wherein each entry correlates a biological extraction to an alimentary element;
and
generating the alimentary profile as a function of the alimentary machine-learning model, the biological extraction of the user, and the alimentary element order chronicle;
determine, using a predictive machine-learning process and the alimentary profile, a predicted alimentary element, wherein the predicted alimentary element is a predictive alimentary element a user is expected to order;
selecting, using the predicted alimentary element, the alternative alimentary element, wherein selecting further comprises:
creating a classifier using a classification machine-learning process as a function of a plurality of alimentary element metrics;
generating a plurality of related alimentary elements as a function of the classifier;
ordering the related alimentary elements as a function of the biological extraction;
and
selecting the alternative alimentary element as a function of the ordering.

11 more elements

A method for predicting alimentary element ordering based on biological extraction, the method comprising:

receiving, by a computing device, a biological extraction of a user;
receiving, by the computing device, an alimentary element order chronicle of a user from a user device;
generating, by the computing device, an alimentary profile, wherein retrieving the alimentary profile comprises:
training an alimentary machine-learning model with first training data that includes a plurality of entries wherein each entry correlates a biological extraction to an alimentary element;
and
generating the alimentary profile as a function of the alimentary machine-learning model, the biological extraction of the user, and the alimentary element order chronicle;
determining, using a predictive machine-learning process and the alimentary profile, a predicted alimentary element, wherein the predicted alimentary element is a predictive alimentary element a user is expected to order
selecting, using the predicted alimentary element, the alternative alimentary element, wherein selecting further comprises:
creating a classifier using a classification machine-learning process as a function of a plurality of alimentary element metrics;
generating a plurality of related alimentary elements as a function of the classifier;
ordering the related alimentary elements as a function of the biological extraction;
and
selecting the alternative alimentary element as a function of the ordering.

10 more elements

Dependencies are inferred from the claim text.

Facts

Application: 17/365,706Filed 1 Jul 2021 · continuation
Priority: 3 Nov 2020
Published: US 2022/0138623 A15 May 2022
Granted: 4 Jul 2023
Term ends: Not estimatedThe source records don’t support an estimate.

Classification17 codes

G06N 20/00
Machine learning
G06F 16/24578
With adaptation to user needs: using ranking
G06F 18/21
Analysing: design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
G06F 18/2113
Selection of the most significant subset of features: by ranking or filtering the set of features, e.g. using a measure of variance or of feature…