Principal component analysis based seed generation for clustering analysis
US8385662B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Apr 30, 2009 |
| Grant date | Feb 26, 2013 |
| Priority date | — |
| Expiry date | Nov 29, 2031 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F18/23213
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Clustering algorithms such as k-means clustering algorithm are used in applications that process entities with spatial and/or temporal characteristics, for example, media objects representing audio, video, or graphical data. Feature vectors representing characteristics of the entities are partitioned using clustering methods that produce results sensitive to an initial set of cluster seeds. The set of initial cluster seeds is generated using principal component analysis of either the complete feature vector set or a subset thereof. The feature vector set is divided into a desired number of initial clusters and a seed determined from each initial cluster.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.