Hybrid learning system for natural language understanding
US10497366B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jan 2, 2019 |
| Grant date | Dec 3, 2019 |
| Priority date | — |
| Expiry date | Jan 2, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG10L2015/225
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
An agent automation system includes a memory configured to store a natural language understanding (NLU) framework, and a processor configured to perform actions, including: generating a meaning representation from an annotated utterance tree of an utterance, wherein a structure of the meaning representation indicates a syntactic structure of the utterance and one or more subtree vectors of the meaning representation indicate a semantic meaning of one or more intent subtrees of the meaning representation; searching the meaning representation of the utterance against an understanding model to extract intents/entities of the utterance based on the one or more subtree vectors of the meaning representation, wherein the understanding model includes a plurality of meaning representations derived from the intent/entity model; and providing the intents/entities of the utterance to a reasoning agent/behavior engine (RA/BE) of the agent automation system that performs one or more actions in response to the intents/entities of the utterance.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.