Parallel-hierarchical model for machine comprehension on small data
US12067490B2 · kind B2 · utility
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20Claims
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Key dates
| Filing date | Oct 17, 2022 |
| Grant date | Aug 20, 2024 |
| Priority date | — |
| Expiry date | Oct 17, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/10
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Examples of the present disclosure provide systems and methods relating to a machine comprehension test with a learning-based approach, harnessing neural networks arranged in a parallel hierarchy. This parallel hierarchy enables the model to compare the passage, question, and answer from a variety of perspectives, as opposed to using a manually designed set of features. Perspectives may range from the word level to sentence fragments to sequences of sentences, and networks operate on word-embedding representations of text. A training methodology for small data is also provided.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.