Machine-learning-based, adaptive updating of quantitative data in database system
US11775516B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Feb 9, 2022 |
| Grant date | Oct 3, 2023 |
| Priority date | — |
| Expiry date | Feb 11, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/00
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Machine-learning-based, adaptive updating of quantitative data in a database system is provided, which includes training one or more machine learning models to facilitate adaptively updating quantitative data in the database system, and ascertaining an update urgency index for updating the quantitative data for one or more data structures of the database system. The update urgency index is representative of an urgency for updating the quantitative data for the data structure(s) and is based, at least in part, on real-time query metrics. The machine learning model(s) is used to adaptively update the quantitative data, where the adaptively updating is based, at least in part, on the ascertained update urgency index. Processing of a database query is optimized in the database system using the adaptively updated quantitative data.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.