Iterative machine learning based techniques for value-based defect analysis in large data sets
US11620558B1 · kind B1 · utility
7Cited by
18References
20Claims
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Key dates
| Filing date | Aug 25, 2020 |
| Grant date | Apr 4, 2023 |
| Priority date | — |
| Expiry date | May 14, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N5/025
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
One or more defect analysis iterations are performed on a collection of records. In a given iteration, a defect presence probability is obtained using a machine learning model for a record group. An estimated audit benefit is then assigned to the record group based at least partly on a defect remediation importance score of the record group. An indication of the estimated audit benefit of the record group is provided to an auditor. An audited defect status for the record group, generated by the auditor, is used to initiate one or more automated actions.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.