Mixed data fingerprinting with principal components analysis
US11157657B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Nov 20, 2017 |
| Grant date | Oct 26, 2021 |
| Priority date | — |
| Expiry date | Aug 9, 2038 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04L2209/608
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Principal components analysis is applied to data sets to fingerprint the dataset or to compare the dataset to a “wild file” that may have been constructed from data found in the dataset. Principal components analysis allows for the reduction of data used for comparison down to a parsimonious compressed signature of a dataset. Datasets with different patterns among the variables will have different patterns of principal components. The principal components of variables (or a relevant subset thereof) in a wild file may be computed and statistically compared to the principal components of identical variables in a data provider's reference file to provide a score. This constitutes a unique and compressed signature of a file that can be used for identification and comparison with similarly defined patterns from other files.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.