Predictive data analysis techniques using bidirectional encodings of structured data fields
US12131229B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jun 29, 2020 |
| Grant date | Oct 29, 2024 |
| Priority date | — |
| Expiry date | Aug 10, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N5/045
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
There is a need for more effective and efficient predictive data analysis based at least in part on structured data. This need can be addressed by, for example, solutions for performing predictive data analysis using bidirectional encoder deep learning models that are configured to process structured data attributes. In one example, a method includes identifying a group of training structured data fields; generating a group of per-field tokenized values for each training structured data field; generating a bidirectional encoder deep learning model based at least in part on each group of per-field tokenized values for a training structured data field; and performing one or more prediction-based actions based at least in part on the trained bidirectional encoder deep learning model.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.