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:
Jul. 14, 2020

Filed:

Jun. 22, 2017
Applicant:

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

Inventors:

Trung Huu Bui, San Jose, CA (US);

Hung Hai Bui, Sunnyvale, CA (US);

Shawn Alan Gaither, Raleigh, NC (US);

Walter Wei-Tuh Chang, San Jose, CA (US);

Michael Frank Kraley, Lexington, MA (US);

Pranjal Daga, West Lafayette, IN (US);

Assignee:

ADOBE INC., San Jose, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/34 (2006.01); G06K 9/00 (2006.01); G06K 9/72 (2006.01); G06Q 10/10 (2012.01); G06Q 10/06 (2012.01); G06F 40/10 (2020.01);
U.S. Cl.
CPC ...
G06K 9/344 (2013.01); G06F 40/10 (2020.01); G06K 9/00456 (2013.01); G06K 9/72 (2013.01); G06Q 10/06 (2013.01); G06Q 10/10 (2013.01);
Abstract

The present invention is directed towards providing automated workflows for the identification of a reading order from text segments extracted from a document. Ordering the text segments is based on trained natural language models. In some embodiments, the workflows are enabled to perform a method for identifying a sequence associated with a portable document. The methods includes iteratively generating a probabilistic language model, receiving the portable document, and selectively extracting features (such as but not limited to text segments) from the document. The method may generate pairs of features (or feature pair from the extracted features). The method may further generate a score for each of the pairs based on the probabilistic language model and determine an order to features based on the scores. The method may provide the extracted features in the determined order.


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