Adversarial training data augmentation data for text classifiers
US11093707B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jan 15, 2019 |
| Grant date | Aug 17, 2021 |
| Priority date | — |
| Expiry date | May 13, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/088
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
An intelligent computer platform to introduce adversarial training to natural language processing (NLP). An initial training set is modified with synthetic training data to create an adversarial training set. The modification includes use of natural language understanding (NLU) to parse the initial training set into components and identify component categories. One or more paraphrase terms are identified with respect to the components and component categories, and function as replacement terms. The synthetic training data is effectively a merging of the initial training set with the replacement terms. As input is presented, a classifier leverages the adversarial training set to identify the intent of the input and to output a classification label to generate accurate and reflective response data.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.