System and method of self-learning conceptual mapping to organize and interpret data
US7447665B2 · kind B2 · utility
Assignee
Inventor
Key dates
| Filing date | May 10, 2005 |
| Grant date | Nov 4, 2008 |
| Priority date | — |
| Expiry date | Aug 29, 2026 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N5/04
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
In a computer implemented method of researching textual data sources, textual data is reduced to a plurality of distinctive words based on frequency of usage within the textual data. The distinctive words are converted into first numeric representations of vectors containing random numbers. A first self-organizing map is formed from the first numeric representations and organized by similarities between the vectors. A second self-organizing map is formed from second numeric representations generated from the organization of the first self-organizing map. The second numeric representations are vectors derived from the first self-organizing map. The vectors are used to train the second self-organizing map. The vectors derived from the first self-organizing map are organized into clusters of similarities between the vectors on the second self-organizing map. Dialectic arguments are formed from the second self-organizing map to interpret the textual data.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.