IP Library Granted Patent US 12,001,966
Granted Patent B2
US 12,001,966 · App. 18/193,147 · Granted Jun 4, 2024

Generation of digital standards using machine-learning model

Inventors: Divyesh Gaur (Pittsburgh, PA); Uxue Zurutuza Dorronsoro (Pittsburgh, PA); Anna Belova (Pittsburgh, PA); Audra Ziegenfuss (Baden, PA); Roshan Bhave (Pittsburgh, PA)
Assignee: SAE International
G06N5/025G06F16/36G06F18/214G06F18/23G06N20/00
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Quick Facts
Patent No.
US 12,001,966
App. No.
18/193,147
Granted
Jun 4, 2024
Kind
B2
Abstract

One embodiment provides a method for generating a digital standard utilizing a trained machine-learning model, the method including: receiving an underlying standard; extracting conceptual units from the underlying standard; classifying, using at least one trained machine-learning model, at least a portion of the extracted conceptual units into one of a plurality of classification groups; storing the classified extracted conceptual units into a data repository as defined by the schema; displaying, within a user interface on a display of an information handling device, a digital standard in a format based upon the schema; and providing, within the user interface, search and filter functions allowing for finding information related to the digital standard. Other aspects are described and claimed.

Claims (44)

1. A method for generating a digital standard utilizing a trained machine-learning model, the method comprising:

receiving an underlying standard;

extracting conceptual units from the underlying standard;

classifying, using at least one trained machine-learning model, at least a portion of the extracted conceptual units into one of a plurality of classification groups, wherein each of the classification groups identifies a function of the extracted conceptual units, included within a given classification group, within the underlying standard;

wherein the classifying comprises classifying conceptual units from the underlying standard based upon sections of a schema corresponding to a digital standard, wherein the schema identifies a format of the digital standard and provides for displaying digital standards consistently across digital standards;

storing the classified extracted conceptual units into a data repository as defined by the schema thereby allowing an access technique to access and retrieve one of the classified extracted conceptual units upon a request to display a digital standard including the one of the classified extracted conceptual units;

displaying, within a user interface on a display of an information handling device, a digital standard in a format based upon the schema, wherein the displaying comprises displaying a plurality of tabs within the user interface, each of the plurality of tabs corresponding to a different aspect of the digital standard, wherein the displaying comprises accessing conceptual units from the data repository corresponding to the digital standard and displaying the conceptual units in a format in accordance with the schema, and within one of the plurality of tabs corresponding to the classification of the conceptual units; and

providing, within the user interface, search and filter functions allowing for finding information related to the digital standard.

2. The method of claim 1 , wherein a conceptual unit comprises a unit of information contained within the underlying standard.

3. The method of claim 1 , wherein the machine-learning model is trained utilizing annotated underlying standards.

4. The method of claim 1 , comprising labeling, using the at least one trained machine-learning model, the extracted conceptual units with a sub-type of the function corresponding to a given extracted conceptual units.

5. The method of claim 1 , wherein the conceptual units comprise at least one of sentences and table components.

6. The method of claim 1 , wherein the classifying is based upon a context of a given extracted conceptual unit within the underlying standard.

7. The method of claim 1 , wherein the classifying comprises identifying, utilizing expression patterns, attributes of extracted conceptual unit.

8. The method of claim 1 , wherein the machine-learning model is trained utilizing patterns.

9. The method of claim 1 , wherein the classifying comprises identifying, utilizing aliasing, extracted conceptual units representing information having similar attributes.

10. The method of claim 1 , comprising refining the at least one trained machine-learning model utilizing subsequently classified extracted conceptual units.

11. A system for generating a digital standard utilizing a trained machine-learning model, the system comprising:

one or more processors;

a memory device that stores instructions executable by the processor to:

receive an underlying standard;

extract conceptual units from the underlying standard;

classify, using at least one trained machine-learning model, at least a portion of the extracted conceptual units into one of a plurality of classification groups, wherein each of the classification groups identifies a function of the extracted conceptual units, included within a given classification group, within the underlying standard;

wherein the classifying comprises classifying conceptual units from the underlying standard based upon sections of a schema corresponding to a digital standard, wherein the schema identifies a format of the digital standard and provides for displaying digital standards consistently across digital standards;

store the classified extracted conceptual units into a data repository as defined by the schema thereby allowing an access technique to access and retrieve one of the classified extracted conceptual units upon a request to display a digital standard including the one of the classified extracted conceptual units;

display, within a user interface on a display of an information handling device, a digital standard in a format based upon the schema, wherein the displaying comprises displaying a plurality of tabs within the user interface, each of the plurality of tabs corresponding to a different aspect of the digital standard, wherein the displaying comprises accessing conceptual units from the data repository corresponding to the digital standard and displaying the conceptual units in a format in accordance with the schema, and within one of the plurality of tabs corresponding to the classification of the conceptual units; and

provide, within the user interface, search and filter functions allowing for finding information related to the digital standard.

12. The system of claim 11 , wherein a conceptual unit comprises a unit of information contained within the underlying standard.

13. The system of claim 11 , wherein the machine-learning model is trained utilizing annotated underlying standards.

14. The system of claim 11 , comprising labeling, using the at least one trained machine-learning model, the extracted conceptual units with a sub-type of the function corresponding to a given extracted conceptual units.

15. The system of claim 11 , wherein the conceptual units comprise at least one of sentences and table components.

16. The system of claim 11 , wherein the classifying is based upon a context of a given extracted conceptual unit within the underlying standard.

17. The system of claim 11 , wherein the classifying comprises identifying, utilizing expression patterns, attributes of extracted conceptual unit.

18. The system of claim 11 , wherein the machine-learning model is trained utilizing patterns.

19. The system of claim 11 , wherein the classifying comprises identifying, utilizing aliasing, extracted conceptual units representing information having similar attributes.

20. A product for generating a digital standard utilizing a trained machine-learning model, the product comprising:

a storage device that stores code, the code being executable by one or more processors and comprising:

code that receives an underlying standard;

code that extracts conceptual units from the underlying standard;

code that classifies, using at least one trained machine-learning model, at least a portion of the extracted conceptual units into one of a plurality of classification groups, wherein each of the classification groups identifies a function of the extracted conceptual units, included within a given classification group, within the underlying standard;

wherein the classifying comprises classifying conceptual units from the underlying standard based upon sections of a schema corresponding to a digital standard, wherein the schema identifies a format of the digital standard and provides for displaying digital standards consistently across digital standards;

code that stores the classified extracted conceptual units into a data repository as defined by the schema thereby allowing an access technique to access and retrieve one of the classified extracted conceptual units upon a request to display a digital standard including the one of the classified extracted conceptual units;

code that displays, within a user interface on a display of an information handling device, a digital standard in a format based upon the schema, wherein the displaying comprises displaying a plurality of tabs within the user interface, each of the plurality of tabs corresponding to a different aspect of the digital standard, wherein the displaying comprises accessing conceptual units from the data repository corresponding to the digital standard and displaying the conceptual units in a format in accordance with the schema, and within one of the plurality of tabs corresponding to the classification of the conceptual units; and

code that provides, within the user interface, search and filter functions allowing for finding information related to the digital standard.

Assignments (3)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Mar 30, 2023
From: ZIEGENFUSS, AUDRA
To: SAE INTERNATIONAL
Reel/Frame 063175/0318 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Mar 30, 2023
From: GAUR, DIVYESH; ZURUTUZA DORRONSORO, UXUE; BELOVA, ANNA; BHAVE, ROSHAN
To: COGNISTIC LLC
Reel/Frame 063175/0659 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Mar 30, 2023
From: COGNISTIC LLC
To: SAE INTERNATIONAL
Reel/Frame 063176/0506 →
Continuity (2)
Continuation 16905559 · Jun 18, 2020
Related Publication 20230237347A1 · Jul 27, 2023