Machine-learning model for performing contextual summarization of text data
US11704351B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 28, 2022 |
| Grant date | Jul 18, 2023 |
| Priority date | — |
| Expiry date | Oct 28, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V20/41
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
In one example, a system can receive a set of text samples and generate a set of summaries based on the set of text samples. The system can then generate a training dataset by iteratively executing a training-sample generation process. Each iteration can involve selecting multiple text samples from the set of text samples, combining the multiple text samples together into a training sample, determining a text category and a summary corresponding to a selected one of the multiple text samples, and including the text category and the summary in the training sample. After generating the training dataset, the system can use it to train a model. The trained model can then receive a target textual dataset and a target category as input, identify a portion of the target textual dataset corresponding to the target category, and generate a summarization of the portion of that target textual dataset.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.