The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Sep. 09, 2025

Filed:

Feb. 15, 2023
Applicant:

Pearson Education, Inc., Bloomington, MN (US);

Inventors:

Stephen Carroll, San Anselmo, CA (US);

David Lovejoy, Parker, CO (US);

Simcha Knif, Montara, CA (US);

Gennadiy Kukartsev, Highland Ranch, CO (US);

Assignee:

PEARSON EDUCATION, INC., Bloomington, MN (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 3/048 (2013.01); G06F 3/0481 (2022.01); G06F 3/0482 (2013.01); G06F 18/20 (2023.01); G06F 18/211 (2023.01); G06F 18/2431 (2023.01); G06F 21/55 (2013.01); G06F 21/56 (2013.01); G06F 21/57 (2013.01); G06N 3/02 (2006.01); G06N 3/08 (2023.01); G06N 5/01 (2023.01); G06N 7/01 (2023.01); G06N 20/00 (2019.01); G06N 20/10 (2019.01); G06N 20/20 (2019.01); G06Q 10/0635 (2023.01); G06Q 10/0639 (2023.01); G06Q 50/20 (2012.01); G09B 7/02 (2006.01); H04L 9/40 (2022.01); H04L 12/18 (2006.01); H04L 51/18 (2022.01); H04L 67/306 (2022.01); H04L 67/50 (2022.01); G09B 5/06 (2006.01); H04L 41/0681 (2022.01);
U.S. Cl.
CPC ...
G06Q 10/06398 (2013.01); G06F 3/048 (2013.01); G06F 3/0481 (2013.01); G06F 3/0482 (2013.01); G06F 18/211 (2023.01); G06F 18/2431 (2023.01); G06F 18/285 (2023.01); G06F 21/552 (2013.01); G06F 21/554 (2013.01); G06F 21/56 (2013.01); G06F 21/577 (2013.01); G06N 3/02 (2013.01); G06N 3/08 (2013.01); G06N 5/01 (2023.01); G06N 7/01 (2023.01); G06N 20/00 (2019.01); G06N 20/10 (2019.01); G06N 20/20 (2019.01); G06Q 10/0635 (2013.01); G06Q 50/205 (2013.01); G09B 7/02 (2013.01); H04L 12/1895 (2013.01); H04L 51/18 (2013.01); H04L 63/0227 (2013.01); H04L 63/0428 (2013.01); H04L 63/10 (2013.01); H04L 63/1416 (2013.01); H04L 63/1433 (2013.01); H04L 63/1441 (2013.01); H04L 63/20 (2013.01); H04L 67/306 (2013.01); H04L 67/535 (2022.05); G09B 5/065 (2013.01); H04L 41/0681 (2013.01);
Abstract

Systems and methods for feature-based alert triggering are disclosed herein. The system can include memory including a model database containing a machine-learning algorithm. The system can include a user device that can receive inputs from a user; and at least one server. The at least one server can: receive electrical signals from the user device, the electrical signals corresponding to a plurality of user inputs provided to the user device; automatically generate input-based features from the received electrical signals; input the input-based features into the machine-learning algorithm; automatically and directly generate a risk prediction with the machine-learning algorithm from the input-based features; and generate and display an alert when the risk prediction exceeds a threshold value.


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