Method for transforming data elements within a classification system based in part on input from a human annotator or expert
US8612373B2 · kind B2 · utility
Assignee
Inventor
Key dates
| Filing date | Jun 3, 2010 |
| Grant date | Dec 17, 2013 |
| Priority date | — |
| Expiry date | Mar 22, 2032 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/00
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method is provided for transforming data elements within a classification system based in part on input from a human annotator or expert. A first concept evolution model as a training set is composed from a first set of selectively determinable annotations and the first concept evolution model. A trained model is generated after training a learning algorithm with the training set and the concept evolution model. A confidence factor is computed that a predicted annotation is accurately identified. A selected element instance and a corresponding suggested annotation are identified to have a low confidence factor. The classifying of the applied annotation is adjusted where a second concept evolution model is composed for more accurate classifying of the data item.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.