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:
Jan. 07, 2025

Filed:

Jul. 29, 2020
Applicant:

Docusign, Inc., San Francisco, CA (US);

Inventors:

Shrinivas Kiran Kaza, Fremont, CA (US);

Eric M. Zenz, Mercer Island, WA (US);

Roshan Satish, Seattle, WA (US);

Michael Anthony Palazzolo, Seattle, WA (US);

Patrick Beukema, Seattle, WA (US);

Kim Cuong Phung, Hayward, CA (US);

Boon Sun Song, San Jose, CA (US);

Taiwo Raphael Alabi, San Jose, CA (US);

Assignee:

Docusign, Inc., San Francisco, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 40/117 (2020.01); G06F 16/93 (2019.01); G06F 18/214 (2023.01); G06N 20/00 (2019.01); G06V 30/414 (2022.01); G06V 30/416 (2022.01);
U.S. Cl.
CPC ...
G06F 40/117 (2020.01); G06F 16/93 (2019.01); G06F 18/214 (2023.01); G06N 20/00 (2019.01); G06V 30/414 (2022.01); G06V 30/416 (2022.01);
Abstract

An auto-tagging engine receives a training set of data comprising documents including a set of tagged fields with each tagged field corresponding to a portion of the document. The auto-tagging engine trains a machine learned model using the training set of data. The trained machine learned model, when applied to a target document in a document management environment, identifies portions of the target document each corresponding to fields of the target document. For each field of the target document, the auto-tagging engine identifies text of the target document associated with the identified portions of the target document corresponding to fields. Natural language processing is performed on the identified text in order to identify field types for the fields. The target document is automatically modified to include a tag identifying the portion of the target document corresponding to each field and identifying a field type of the field.


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