Machine learning based extraction of partition objects from electronic documents
US10614345B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Apr 12, 2019 |
| Grant date | Apr 7, 2020 |
| Priority date | — |
| Expiry date | Apr 12, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V30/43
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
An object-extraction method includes generating multiple partition objects based on an electronic document, and receiving a first user selection of a data element via a user interface of a compute device. In response to the first user selection, and using a machine learning model, a first subset of partition objects from the multiple partition objects is detected and displayed via the user interface. A user interaction, via the user interface, with one of the partition objects is detected, and in response, a weight of the machine learning model is modified, to produce a modified machine learning model. A second user selection of the data element is received via the user interface, and in response and using the modified machine learning model, a second subset of partition objects from the multiple partition objects is detected and displayed via the user interface, the second subset different from the first subset.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.