Leveraging a collection of training tables to accurately predict errors within a variety of tables
US11698892B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 25, 2021 |
| Grant date | Jul 11, 2023 |
| Priority date | — |
| Expiry date | Oct 25, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/00
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The present disclosure relates to systems, methods, and computer-readable media for using a variety of hypothesis tests to identify errors within tables and other structured datasets. For example, systems disclosed herein can generate a modified table from an input table by removing one or more entries from the input table. The systems disclosed herein can further leverage a collection of training tables to determine probabilities associated with whether the input table and modified table are drawn from the collection of training tables. The systems disclosed herein can additionally compare the probabilities to accurately determine whether the one or more entries include errors therein. The systems disclosed herein may apply to a variety of different sizes and types of tables to identify different types of common errors within input tables.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.