Mixtures of Bayesian networks
US6807537B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 4, 1997 |
| Grant date | Oct 19, 2004 |
| Priority date | — |
| Expiry date | Dec 4, 2017 |
Classification
- Technology area (CPC Y)Emerging Cross-Sectional Technologies
- CPC primaryY10S707/99948
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
One aspect of the invention is the construction of mixtures of Bayesian networks. Another aspect of the invention is the use of such mixtures of Bayesian networks to perform inferencing. A mixture of Bayesian networks (MBN) consists of plural hypothesis-specific Bayesian networks (HSBNs) having possibly hidden and observed variables. A common external hidden variable is associated with the MBN, but is not included in any of the HSBNs. The number of HSBNs in the MBN corresponds to the number of states of the common external hidden variable, and each HSBN is based upon the hypothesis that the common external hidden variable is in a corresponding one of those states. In one mode of the invention, the MBN having the highest MBN score is selected for use in performing inferencing. In another mode of the invention, some or all of the MBNs are retained as a collection of MBNs which perform inferencing in parallel, their outputs being weighted in accordance with the corresponding MBN scores and the MBN collection output being the weighted sum of all the MBN outputs. In one application of the invention, collaborative filtering may be performed by defining the observed variables to be choice…
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.