Hybrid clustering for data analytics
US9489627B2 · kind B2 · utility
Assignee
Inventor
Key dates
| Filing date | Jul 1, 2013 |
| Grant date | Nov 8, 2016 |
| Priority date | — |
| Expiry date | Dec 28, 2034 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG16B40/00
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The invention includes methods and systems for analyzing data to determine trends in the data and to identify outliers. The methods and systems include a learning algorithm whereby a data space is co-populated with artificial, evenly distributed data, and then the data space is carved into smaller portions whereupon the number of real and artificial data points are compared. Through an iterative process, clusters having less than evenly distributed real data are discarded. Additionally, a final quality control measurement is used to merge clusters that are too similar to be meaningful. The invention is widely applicable to data analytics, generally, including financial transactions, retail sales, elections, and sports.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.