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:
Nov. 30, 2021

Filed:

Aug. 31, 2018
Applicant:

Pearson Education, Inc., New York, NY (US);

Inventors:

Alison Doucette, Stow, MA (US);

Victoria Kortan, Centennial, CO (US);

Daniel Ensign, Fort Lupton, CO (US);

Mark Potter, Pittsburgh, PA (US);

Chadwick Reimers, Larkspur, CO (US);

Brian Moriarty, Fort Lee, NJ (US);

Assignee:

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

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 15/16 (2006.01); G06N 7/08 (2006.01); G06K 9/62 (2006.01); G06N 7/00 (2006.01); G06F 16/35 (2019.01); G06F 16/9535 (2019.01); G06Q 10/10 (2012.01); G06N 5/00 (2006.01); G06N 5/04 (2006.01); G06N 20/20 (2019.01); G06F 40/131 (2020.01); G06F 40/137 (2020.01); G06F 40/205 (2020.01); G06F 40/289 (2020.01); G06N 3/02 (2006.01); G06N 5/02 (2006.01);
U.S. Cl.
CPC ...
G06N 7/08 (2013.01); G06F 16/35 (2019.01); G06F 16/9535 (2019.01); G06F 40/131 (2020.01); G06F 40/137 (2020.01); G06F 40/205 (2020.01); G06F 40/289 (2020.01); G06K 9/6282 (2013.01); G06N 5/003 (2013.01); G06N 5/046 (2013.01); G06N 7/005 (2013.01); G06N 20/20 (2019.01); G06Q 10/1097 (2013.01); G06N 3/02 (2013.01); G06N 5/022 (2013.01); G06N 5/045 (2013.01);
Abstract

Systems and methods for content provisioning are disclosed herein. The method includes receiving content corresponding to at least one source document, parsing the content, identifying segments from the parsed content, generating a networked grouping of the segments, receiving historical user information about a plurality of users, training a model by using the historical user information, receiving activities of a user, parsing the activities of the user, identifying components from the parsed activities, correlating the components with the segments, extracting features from the activities of the user based on the correlation, and using the trained model to estimate a mastery level of the user based on the features.


Find Patent Forward Citations

Loading…