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:
Dec. 24, 2024

Filed:

Jan. 19, 2022
Applicant:

Servicenow, Inc., Santa Clara, CA (US);

Inventors:

Roshnee Sharma, Redmond, WA (US);

Edwin Sapugay, Foster City, CA (US);

Sathwik Tejaswi Madhusudhan, Santa Clara, CA (US);

Anil Kumar Madamala, Sunnyvale, CA (US);

Hari Subramani, Champaign, IL (US);

Jonggun Park, Santa Clara, CA (US);

Srinivas Satyasai Sunkara, Saratoga, CA (US);

Assignee:

ServiceNow, Inc., Santa Clara, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 40/30 (2020.01); G06F 40/40 (2020.01); H04L 51/10 (2022.01);
U.S. Cl.
CPC ...
G06F 40/30 (2020.01); G06F 40/40 (2020.01); H04L 51/10 (2013.01);
Abstract

A natural language understanding (NLU) framework includes a modeling and optimization system that enables enhanced understanding and explainability to the operation of the NLU framework. The NLU framework includes a configuration vector storing settings of various components that may be applied during NLU inference of an utterance, such as which components should be activated or deactivated, as well as which numerical values (e.g., threshold values, coefficients, weight values) that are used by these components during operation. By using this configuration vector to systematically disable and adjust numerical parameters of the components of the NLU framework, and then determining the performance of the NLU framework in these configurations, the modeling and optimization system determines relationships between, as well as the relative importance of, the components of the NLU framework. The modeling and optimization system automatically determines or optimizes configurations for the NLU framework to accommodate various NLU performance and/or resource constraints.


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