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:
Nov. 10, 2020

Filed:

Jun. 15, 2018
Applicant:

International Business Machines Corporation, Armonk, NY (US);

Inventors:

Craig M. Trim, Sylmar, CA (US);

Peter C. Boyle, British Columbia, CA;

Brenda Haddock, Indianapolis, IN (US);

Maria Wittnebert, Ridgewood, NJ (US);

Eniko I. Rozsa, Coquitlam, CA;

Diman Ghazi, Vancouver, CA;

Abhishek Basu, Kolkata, IN;

Xavier Verges Farrero, Barcelona, ES;

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G06F 17/28 (2006.01); G06F 16/332 (2019.01); G06F 11/32 (2006.01); G06F 11/34 (2006.01);
U.S. Cl.
CPC ...
G06F 16/3329 (2019.01); G06F 11/321 (2013.01); G06F 11/3409 (2013.01); G06F 16/3325 (2019.01);
Abstract

A computer-implemented method includes: generating, by a computing device, a sample of a query, wherein the query maps to a predetermined categorization; processing the sample with a first natural language process, wherein the processing produces an output comprising a categorization of the sample; storing data regarding whether the categorization of the output matches the predetermined categorization; generating a report based on the stored data indicating a percentage of a plurality of samples of the query whose categorizations match the predetermined characterization; outputting the report; and receiving a second natural language process comprising updates to the first natural language process based on the report, wherein the updates increase the percentage of the plurality of samples that match the predetermined categorization when processed with the second natural language process relative to when the plurality of samples was processed with the first natural language process.


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