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.
Patent No.:
Date of Patent:
Jan. 14, 2025
Filed:
Jan. 19, 2022
Servicenow, Inc., Santa Clara, CA (US);
Jonggun Park, Santa Clara, CA (US);
Edwin Sapugay, Foster City, CA (US);
Phani Bhushan Kumar Nivarthi, Fremont, CA (US);
Masayo Iida, Mountain View, CA (US);
Sathwik Tejaswi Madhusudhan, Santa Clara, CA (US);
ServiceNow, Inc., Santa Clara, CA (US);
Abstract
A natural language understanding (NLU) framework includes an a concept system that performs concept matching of user utterances. The concept system generates a concept cluster model from sample utterances of an intent-entity model, and then trains a machine learning (ML) concept model based on the concept cluster model. Once trained, the concept model receives semantic vectors representing potential concepts extracted from utterances, and provides concept indicators to an ensemble scoring system. These concept indicators include indications of which concepts of the concept model that matched to the potential concepts, which intents of the intent-entity model are related to these concepts, and concept-relationship scores indicating a strength and/or uniqueness of the relationship between each concept-intent combination. Based on these concept-related indicators, the ensemble scoring system may determine and apply an ensemble scoring adjustment when determining an ensemble artifact score for each of the artifacts extracted from an utterance.