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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.

Patent No.:

US 11630952 B1

PDFFull Text
Date of Patent:
Apr. 18, 2023

Filed:

Jul. 22, 2019

Classifying terms from source texts using implicit and explicit class-recognition-machine-learning models

Applicant:

Adobe Inc., San Jose, CA (US);

Inventors:

Sean MacAvaney, Washington, DC (US);

Franck Dernoncourt, Sunnyvale, CA (US);

Walter Chang, San Jose, CA (US);

Seokhwan Kim, San Jose, CA (US);

Doo Soon Kim, San Jose, CA (US);

Chen Fang, Hanover, NH (US);

Assignee:

Adobe Inc., San Jose, CA (US);

Attorney:

Keller Preece PLLC

Primary Examiner:

Omar S Ismail

Int. Cl.
CPC ...
G06F 17/15 (2006.01); G06F 17/16 (2006.01); G06N 3/045 (2023.01); G06V 10/80 (2022.01); G06V 10/82 (2022.01); G06F 40/279 (2020.01); G06F 18/2431 (2023.01); G06V 10/764 (2022.01); G06V 10/70 (2022.01);
U.S. Cl.
CPC ...
G06F 40/279 (2020.01); G06F 17/15 (2013.01); G06F 17/16 (2013.01); G06F 18/2431 (2023.01); G06N 3/045 (2023.01); G06V 10/764 (2022.01); G06V 10/768 (2022.01); G06V 10/809 (2022.01); G06V 10/82 (2022.01);
Abstract

This disclosure relates to methods, non-transitory computer readable media, and systems that can classify term sequences within a source text based on textual features analyzed by both an implicit-class-recognition model and an explicit-class-recognition model. For example, by applying machine-learning models for both implicit and explicit class recognition, the disclosed systems can determine a class corresponding to a particular term sequence within a source text and identify the particular term sequence reflecting the class. The dual-model architecture can equip the disclosed systems to apply (i) the implicit-class-recognition model to recognize implicit references to a class in source texts and (ii) the explicit-class-recognition model to recognize explicit references to the same class in source texts.

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