Analysis of retail transactions using gaussian mixture models in a data mining system
US6947878B2 · kind B2 · utility
1Cited by
6References
12Claims
0Family size
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Key dates
| Filing date | Dec 18, 2000 |
| Grant date | Sep 20, 2005 |
| Priority date | — |
| Expiry date | Aug 19, 2023 |
Classification
- Technology area (CPC Y)Emerging Cross-Sectional Technologies
- CPC primaryY10S707/99936
- WIPO fieldIT methods for management
- WIPO sectorElectrical engineering
Abstract
A computer-implemented data mining system that analyzes data using Gaussian Mixture Models. The data is accessed from a database, and then an Expectation-Maximization (EM) algorithm is performed in the computer-implemented data mining system to create the Gaussian Mixture Model for the accessed data. The EM algorithm generates an output that describes clustering in the data by computing a mixture of probability distributions fitted to the accessed data.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.