US 2014/0229147 A1Published application

Approximating value densities

AssigneeOracle International Corporation

InventorsBoriana Lubomirova Milenova, Marcos M. Campos, Joseph Yarmus

Life of this patent

Estimating the term…

Loading patent…

Abstract

Processes, machines, and stored machine instructions are provided for approximating value densities in data. While generating a resulting density model to approximate value densities in a set of data, density modeling logic selects a functional component of a first model to vary based at least in part on how much the functional component contributes to how well the first model approximates the value densities. The density modeling logic then uses at least the functional component and a variation of the functional component as seed components to determine adjusted functional components of a second model by iteratively determining, in an expectation step, how much the seed components contribute to how well the second model explains the values, and, in a maximization step, new seed components, optionally to be used in further iterations, based at least in part on how much of the values are attributable to the seed components.

Claims26

Dependent claims

A method comprising:

generating a first density model that approximates value densities in a set of data, wherein the first density model comprises a first set of functional components;
selecting a first functional component of the first set of functional components based at least in part on how much the first functional component contributes to how well the first set of functional components approximates the value densities in the set of data;
generating a second density model comprising a second set of functional components, wherein the second set of functional components includes at least one more functional component than the first set of functional components, and wherein the second set of functional components is determined using at least the first functional component and a variation of the first functional component as seed components;
storing, in association with the set of data, a resulting density model that is generated based at least in part on the steps of generating the first density model, selecting the first functional component, and generating the second density model;
wherein the method is performed by one or more computing devices.

2 more elements

One or more non-transitory storage media storing instructions which, when executed by one or more computing devices, cause performance of steps comprising:

generating a first density model that approximates value densities in a set of data, wherein the first density model comprises a first set of functional components;
selecting a first functional component of the first set of functional components based at least in part on how much the first functional component contributes to how well the first set of functional components approximates the value densities in the set of data;
generating a second density model comprising a second set of functional components, wherein the second set of functional components includes at least one more functional component than the first set of functional components, and wherein the second set of functional components is determined using at least the first functional component and a variation of the first functional component as seed components;
storing, in association with the set of data, a resulting density model that is generated based at least in part on the steps of generating the first density model, selecting the first functional component, and generating the second density model.

1 more element

Dependencies are inferred from the claim text.