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:
Mar. 14, 2023

Filed:

Feb. 21, 2020
Applicants:

Ramaswamy Venkateshwaran, Dublin, CA (US);

Sridevi Ramaswamy, Dublin, CA (US);

Priya Rani, Fremont, CA (US);

Huanchen LI, Hayward, CA (US);

KE Chen, Fremont, CA (US);

Inventors:

Ramaswamy Venkateshwaran, Dublin, CA (US);

Sridevi Ramaswamy, Dublin, CA (US);

Priya Rani, Fremont, CA (US);

Huanchen Li, Hayward, CA (US);

Ke Chen, Fremont, CA (US);

Assignee:

Other;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 40/30 (2020.01); G06F 16/35 (2019.01); G06F 40/117 (2020.01); G06F 16/33 (2019.01); G06V 10/40 (2022.01); G06V 30/10 (2022.01);
U.S. Cl.
CPC ...
G06F 40/30 (2020.01); G06F 16/3344 (2019.01); G06F 16/35 (2019.01); G06F 40/117 (2020.01); G06V 10/40 (2022.01); G06V 30/10 (2022.01);
Abstract

A computerized method for reducing domain noise, creating and summarizing human-written sentences into clusters for efficient tagging in natural language processing comprising: receiving a typed, handwritten or printed text; implementing an optical character recognition (OCR) process on human written text to generate a digital version of the human written text; splitting the digital version of the typed, handwritten or printed text into an array of sentences, using a sentence splitter to generate a split sentence version; determining a domain of the human written text; based on the domain, implementing a domain noise reduction process on the split sentences version; hierarchically clustering the split sentences version after the domain noise reduction process; and summarizing the clustered sentences and reducing the amount of data to be tagged.


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