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. 12, 2022

Filed:

May. 05, 2020
Applicant:

At&t Intellectual Property I, L.p., Atlanta, GA (US);

Inventors:

Sanjeev Misra, Somerset, NJ (US);

Appavu Siva Prakasam, New Providence, NJ (US);

Ann Eileen Skudlark, San Ramon, CA (US);

Siva Kolachina, Plano, TX (US);

Nisha Shahul Hameed, Bellevue, WA (US);

Prashanth Boddhireddy, Plano, TX (US);

Lien Tran, Seattle, WA (US);

Jenq-Chyuan Wang, East Hanover, NJ (US);

Assignee:
Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G06Q 30/02 (2012.01); G06F 16/35 (2019.01); G06F 16/93 (2019.01); G06F 40/295 (2020.01); G06N 5/04 (2006.01); G06Q 10/10 (2012.01); G06N 20/00 (2019.01);
U.S. Cl.
CPC ...
G06Q 30/0269 (2013.01); G06F 16/355 (2019.01); G06F 16/93 (2019.01); G06F 40/295 (2020.01); G06N 5/04 (2013.01); G06N 20/00 (2019.01); G06Q 10/107 (2013.01); G06Q 30/0275 (2013.01);
Abstract

Aspects of the subject disclosure may include, for example, determining classes from a corpus based on topic modeling, data clustering and unsupervised learning. Labels are determined for each of the classes and trained models are generated for each of the classes by assignment of a plurality of textual documents to labels based on a highest number of matches. A raw textual document can be tokenized and stop words removed. A corresponding one of the trained models can be selected according to a class that is applicable to subject matter of the raw textual document. The processed document can be assigned to a target label based on a highest number of matches of words. Other embodiments are disclosed.


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