Systems and methods for data transformation using higher order learning
US8572071B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jun 9, 2010 |
| Grant date | Oct 29, 2013 |
| Priority date | — |
| Expiry date | Mar 15, 2031 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F18/254
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Disclosed is a method and apparatus for transforming data in vector form. Each vector is composed of a set of attributes that are either boolean or have been mapped to boolean form. The vectors may or may not fall into categories assigned by a subject matter expert (SME). If categories exist, the categorical labels divide the vectors into subsets. The first transformation calculates a prior probability for each attribute based on the links between attributes in each subset of the vectors. The second transformation computes a new numeric value for each attribute based on the links between attributes in each subset of the vectors. The third transformation operates on vectors that have not been categorized. Based on the automatic selection of categories from the attributes, this transformation computes a new numeric value for each attribute based on the links between attributes in each subset of the vectors.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.