Method, system and computer program product for non-linear mapping of multi-dimensional data
US7117187B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | May 2, 2003 |
| Grant date | Oct 3, 2006 |
| Priority date | — |
| Expiry date | May 2, 2023 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F18/2137
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method, system and computer program product are provided for scaling, or dimensionally reducing, multi-dimensional data sets that scale well for large data sets. The invention scales multi-dimensional data sets by determining one or more non-linear functions between a sample of points from the multi-dimensional data set and a corresponding set of dimensionally reduced points. Thereafter, these one or more non-linear functions are used to non-linearly map additional points. The additional points may be members of the original multi-dimensional data set or may be new, previously unseen points. In an embodiment, the determination of the non-linear relationship between the sample of points from the multi-dimensional data set and the corresponding set of dimensionally reduced points is performed by a self-learning system such as a neural network. The additional points are mapped using the self-learning system in a feed-forward/predictive manner.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.